#options(warn=-1) #remove warnings
options(warn=0) #print warnings
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#to add or remove commenting for multiple lines of code: ctl+shift+c
library(readxl)
library(dplyr)
##
## Attachement du package : 'dplyr'
## Les objets suivants sont masqués depuis 'package:stats':
##
## filter, lag
## Les objets suivants sont masqués depuis 'package:base':
##
## intersect, setdiff, setequal, union
library(tidyr)
## Warning: le package 'tidyr' a été compilé avec la version R 4.3.3
library(tibble)
library(stringr)
library(ggplot2)
## Warning: le package 'ggplot2' a été compilé avec la version R 4.3.3
library(ggbreak)
## Warning: le package 'ggbreak' a été compilé avec la version R 4.3.3
## ggbreak v0.1.2
##
## If you use ggbreak in published research, please cite the following
## paper:
##
## S Xu, M Chen, T Feng, L Zhan, L Zhou, G Yu. Use ggbreak to effectively
## utilize plotting space to deal with large datasets and outliers.
## Frontiers in Genetics. 2021, 12:774846. doi: 10.3389/fgene.2021.774846
library(lubridate)
##
## Attachement du package : 'lubridate'
## Les objets suivants sont masqués depuis 'package:base':
##
## date, intersect, setdiff, union
library(hms)
##
## Attachement du package : 'hms'
## L'objet suivant est masqué depuis 'package:lubridate':
##
## hms
library(chron)
##
## Attachement du package : 'chron'
## Les objets suivants sont masqués depuis 'package:lubridate':
##
## days, hours, minutes, seconds, years
library(janitor)
## Warning: le package 'janitor' a été compilé avec la version R 4.3.3
##
## Attachement du package : 'janitor'
## Les objets suivants sont masqués depuis 'package:stats':
##
## chisq.test, fisher.test
library(apyramid)
## Warning: le package 'apyramid' a été compilé avec la version R 4.3.3
library(FactoMineR)
## Warning: le package 'FactoMineR' a été compilé avec la version R 4.3.3
library(factoextra)
## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
library(fmsb)
## Warning: le package 'fmsb' a été compilé avec la version R 4.3.3
library(stringi)
## Warning: le package 'stringi' a été compilé avec la version R 4.3.3
library(nnet)
## Warning: le package 'nnet' a été compilé avec la version R 4.3.3
library(MASS)
##
## Attachement du package : 'MASS'
## L'objet suivant est masqué depuis 'package:dplyr':
##
## select
library(car)
## Warning: le package 'car' a été compilé avec la version R 4.3.3
## Le chargement a nécessité le package : carData
##
## Attachement du package : 'car'
## L'objet suivant est masqué depuis 'package:dplyr':
##
## recode
library(tidyverse)
## Warning: le package 'tidyverse' a été compilé avec la version R 4.3.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats 1.0.0 ✔ readr 2.1.5
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ chron::days() masks lubridate::days()
## ✖ dplyr::filter() masks stats::filter()
## ✖ hms::hms() masks lubridate::hms()
## ✖ chron::hours() masks lubridate::hours()
## ✖ dplyr::lag() masks stats::lag()
## ✖ chron::minutes() masks lubridate::minutes()
## ✖ car::recode() masks dplyr::recode()
## ✖ chron::seconds() masks lubridate::seconds()
## ✖ MASS::select() masks dplyr::select()
## ✖ purrr::some() masks car::some()
## ✖ chron::years() masks lubridate::years()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(knitr)
## Warning: le package 'knitr' a été compilé avec la version R 4.3.3
library(kableExtra)
## Warning: le package 'kableExtra' a été compilé avec la version R 4.3.3
##
## Attachement du package : 'kableExtra'
##
## L'objet suivant est masqué depuis 'package:dplyr':
##
## group_rows
library(broom)
## Warning: le package 'broom' a été compilé avec la version R 4.3.3
library(gtsummary)
## Warning: le package 'gtsummary' a été compilé avec la version R 4.3.3
##
## Attachement du package : 'gtsummary'
##
## L'objet suivant est masqué depuis 'package:MASS':
##
## select
library(ggeffects)
## Warning: le package 'ggeffects' a été compilé avec la version R 4.3.3
library(marginaleffects)
## Warning: le package 'marginaleffects' a été compilé avec la version R 4.3.3
library(rpart)
## Warning: le package 'rpart' a été compilé avec la version R 4.3.3
library(rpart.plot)
## Warning: le package 'rpart.plot' a été compilé avec la version R 4.3.3
`%notin%` <- Negate(`%in%`)
# import DBs and work on DBs ####
# survey
#NB among corrections to brought to the excel file prior importation, I had to correct for date, cfr in the excel file %d-%m-%y; however, some ":" as separator, empty " " space before the date etc. So in any case check for these for further data importation.
Meta.survey <- read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "Metha_enquete_terrain_publique", col_names = T, range = "A14:D218")
Meta.survey <- arrange(Meta.survey, Libellé)
Meta.survey$Libellé
## [1] "a" "a" "abondance"
## [4] "accessibilite" "act_peche" "act_pro"
## [7] "agachon" "age" "age_moyen"
## [10] "anc_posid" "aoursin" "apm"
## [13] "assoc" "aube" "autre"
## [16] "autre" "autre" "autre_app"
## [19] "autre_tech" "avis_mes_l" "avis_mes_o"
## [22] "avis_pnm" "bag_thon" "broume"
## [25] "cat_pro" "chas_trou" "co_pnmcca"
## [28] "code_insee" "comm_gest" "comm_rais_var"
## [31] "commune" "connaissance" "crepuscule"
## [34] "csm" "d" "date"
## [37] "deb_age" "deb_sortie" "debarq"
## [40] "dep_csm" "dep_pdb" "dep_pe"
## [43] "dep_po" "direct_h" "direct_v"
## [46] "doursin" "douz_jour" "dur_moy_o"
## [49] "dur_sort" "esp_cib" "esp_n_ind"
## [52] "espcib1" "espcib2" "espcib3"
## [55] "etat_mer" "f" "fiche_n"
## [58] "fin_sortie" "fireball" "flotteur"
## [61] "fonds_rech" "force_v" "foursin"
## [64] "gps" "h_debut" "h_fin"
## [67] "heure_enq" "id_obs" "id_sortie"
## [70] "inchiku" "indienne" "inf_pech_l"
## [73] "j" "j" "j"
## [76] "jigging" "journée" "joursin"
## [79] "lat" "leur_surf" "leurre_tt"
## [82] "ligne_m" "loca_bat" "loca_dom"
## [85] "longueur" "m" "m"
## [88] "madai" "matin" "mod_peche"
## [91] "mode_eqt" "mort_cru" "mort_esp"
## [94] "mort_mll" "mort_pss" "mort_vers"
## [97] "motor" "moursin" "n"
## [100] "nasse" "nb_ours" "nb_pech_o"
## [103] "nb_pecheur" "nb_sort_an" "nb_sort_an"
## [106] "nb_sous_tail" "neb" "nimp_q"
## [109] "niql" "nom_asso" "nom_esp_ind"
## [112] "nuit" "o" "obs"
## [115] "obs_stock_l" "obs_stock_o" "p_no_kill"
## [118] "palangre" "palangro" "pdb"
## [121] "pe" "peche_cal" "pelote"
## [124] "phase_lune" "pierre" "pierre_bd"
## [127] "po" "port_atta" "poss_bat"
## [130] "pour_jf" "pourc_sem" "pourc_we"
## [133] "prise_jour" "procu_app" "prof_m"
## [136] "prof_m_moyen" "proximite" "q_esp"
## [139] "quot_max_o" "raison_var" "recommandation"
## [142] "reg_pech_l" "reg_pech_o" "res_alien"
## [145] "res_tour" "rockfish" "s"
## [148] "sais_pech_o" "secteur_po" "sem"
## [151] "sexe" "shad" "shore_jigg"
## [154] "soir" "solu_gest" "sondeur"
## [157] "sout_bd" "surfcas" "table_traçante"
## [160] "tail_min_o" "temp" "temps_parc"
## [163] "temps_peche_estime" "temps_pêche" "tenya"
## [166] "tra_fond" "tra_surf" "tranquilite"
## [169] "turlutte" "type_bat" "vac"
## [172] "vire_ligne" "viv_cru" "viv_esp"
## [175] "viv_moll" "viv_pss" "viv_vers"
## [178] "vivier" "we" "x_degre"
## [181] "x_lon" "x_lon_DD" "x_min_dec"
## [184] "y_degre" "y_lat" "y_lat_DD"
## [187] "y_min_dec" "z_1" "z_2"
## [190] "z_3" "z_4" "z_54"
## [193] "z_55" "z_56" "z_57"
## [196] "z_58" "z_59" "z_6"
## [199] "z_60" "z_61" "z_7"
## [202] "z_8" "z_9" "zone_pro"
survey <- (read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "BDD_enquete_terrain_publique", col_names = T))[ , order(names(read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "BDD_enquete_terrain_publique", col_names = T)))]
names(survey)
## [1] "a" "a5" "abondance"
## [4] "accessibilite" "act_peche" "act_pro"
## [7] "agachon" "age" "age_moyen"
## [10] "anc_posid" "aoursin" "apm"
## [13] "assoc" "aube" "autre"
## [16] "autre_app" "autre_tech" "autre10"
## [19] "autre9" "avis_mes_l" "avis_mes_o"
## [22] "avis_pnm" "bag_thon" "broume"
## [25] "cat_pro" "chas_trou" "co_pnmcca"
## [28] "code_insee" "comm_gest" "comm_rais_var"
## [31] "commune" "connaissance" "crepuscule"
## [34] "csm" "d" "date"
## [37] "deb_age" "deb_sortie" "debarq"
## [40] "dep_csm" "dep_pdb" "dep_pe"
## [43] "dep_po" "direct_h" "direct_v"
## [46] "doursin" "douz_jour" "douz_jour8"
## [49] "dur_moy_o" "dur_sort" "esp_cib"
## [52] "esp_n_ind" "espcib1" "espcib2"
## [55] "espcib3" "etat_mer" "f"
## [58] "fiche_n" "fin_sortie" "fireball"
## [61] "flotteur" "fonds_rech" "force_v"
## [64] "foursin" "gps" "h_debut"
## [67] "h_fin" "heure_enq" "id_obs"
## [70] "id_sortie" "inchiku" "indienne"
## [73] "inf_pech_l" "j" "j3"
## [76] "j4" "jigging" "journee"
## [79] "joursin" "lat" "leur_surf"
## [82] "leurre_tt" "ligne_m" "loca_bat"
## [85] "loca_dom" "longueur" "m"
## [88] "m2" "madai" "matin"
## [91] "mod_peche" "mode_eqt" "mort_cru"
## [94] "mort_esp" "mort_mll" "mort_pss"
## [97] "mort_vers" "motor" "moursin"
## [100] "n" "nasse" "nb_ours"
## [103] "nb_pech_o" "nb_pecheur" "nb_sort_an"
## [106] "nb_sort_an6" "nb_sous_tail" "neb"
## [109] "nimp_q" "niql" "nom_asso"
## [112] "nom_esp_ind" "nuit" "o"
## [115] "obs" "obs_stock_l" "obs_stock_o"
## [118] "p_no_kill" "palangre" "palangro"
## [121] "pdb" "pe" "peche_cal"
## [124] "pelote" "phase_lune" "pierre"
## [127] "pierre_bd" "po" "port_atta"
## [130] "poss_bat" "pour_jf" "pourc_sem"
## [133] "pourc_we" "prise_jour" "procu_app"
## [136] "prof_m_moyen" "proximite" "q_esp"
## [139] "quot_max_o" "raison_var" "recommandation"
## [142] "reg_pech_l" "reg_pech_o" "res_alien"
## [145] "res_tour" "rockfish" "s"
## [148] "sais_pech_o" "Saisie" "secteur_po"
## [151] "secteur_po7" "sem" "sexe"
## [154] "shad" "shore_jigg" "soir"
## [157] "solu_gest" "sondeur" "sout_bd"
## [160] "surfcas" "table_traçante" "tail_min_o"
## [163] "temp" "temps_parc" "Temps_peche_effectif"
## [166] "Temps_peche_estime" "tenya" "tra_fond"
## [169] "tra_surf" "tranquilite" "turlutte"
## [172] "type_bat" "vac" "vire_ligne"
## [175] "viv_cru" "viv_esp" "viv_moll"
## [178] "viv_pss" "viv_vers" "vivier"
## [181] "we" "x_degres" "x_lon"
## [184] "x_lon_DD" "x_min_dec" "y_degres"
## [187] "y_lat" "y_lat_DD" "y_min_dec"
## [190] "z_1" "z_2" "z_3"
## [193] "z_4" "z_54" "z_55"
## [196] "z_56" "z_57" "z_58"
## [199] "z_59" "z_6" "z_60"
## [202] "z_61" "z_7" "z_8"
## [205] "z_9" "zone_pro"
sapply(survey, class)
## $a
## [1] "character"
##
## $a5
## [1] "character"
##
## $abondance
## [1] "character"
##
## $accessibilite
## [1] "character"
##
## $act_peche
## [1] "character"
##
## $act_pro
## [1] "character"
##
## $agachon
## [1] "character"
##
## $age
## [1] "character"
##
## $age_moyen
## [1] "character"
##
## $anc_posid
## [1] "character"
##
## $aoursin
## [1] "character"
##
## $apm
## [1] "character"
##
## $assoc
## [1] "character"
##
## $aube
## [1] "character"
##
## $autre
## [1] "character"
##
## $autre_app
## [1] "character"
##
## $autre_tech
## [1] "character"
##
## $autre10
## [1] "character"
##
## $autre9
## [1] "character"
##
## $avis_mes_l
## [1] "character"
##
## $avis_mes_o
## [1] "character"
##
## $avis_pnm
## [1] "character"
##
## $bag_thon
## [1] "character"
##
## $broume
## [1] "character"
##
## $cat_pro
## [1] "character"
##
## $chas_trou
## [1] "character"
##
## $co_pnmcca
## [1] "character"
##
## $code_insee
## [1] "character"
##
## $comm_gest
## [1] "character"
##
## $comm_rais_var
## [1] "character"
##
## $commune
## [1] "character"
##
## $connaissance
## [1] "character"
##
## $crepuscule
## [1] "character"
##
## $csm
## [1] "character"
##
## $d
## [1] "character"
##
## $date
## [1] "character"
##
## $deb_age
## [1] "character"
##
## $deb_sortie
## [1] "character"
##
## $debarq
## [1] "character"
##
## $dep_csm
## [1] "character"
##
## $dep_pdb
## [1] "character"
##
## $dep_pe
## [1] "character"
##
## $dep_po
## [1] "character"
##
## $direct_h
## [1] "character"
##
## $direct_v
## [1] "character"
##
## $doursin
## [1] "character"
##
## $douz_jour
## [1] "character"
##
## $douz_jour8
## [1] "character"
##
## $dur_moy_o
## [1] "character"
##
## $dur_sort
## [1] "character"
##
## $esp_cib
## [1] "character"
##
## $esp_n_ind
## [1] "character"
##
## $espcib1
## [1] "character"
##
## $espcib2
## [1] "character"
##
## $espcib3
## [1] "character"
##
## $etat_mer
## [1] "character"
##
## $f
## [1] "character"
##
## $fiche_n
## [1] "character"
##
## $fin_sortie
## [1] "character"
##
## $fireball
## [1] "character"
##
## $flotteur
## [1] "character"
##
## $fonds_rech
## [1] "character"
##
## $force_v
## [1] "character"
##
## $foursin
## [1] "character"
##
## $gps
## [1] "character"
##
## $h_debut
## [1] "POSIXct" "POSIXt"
##
## $h_fin
## [1] "POSIXct" "POSIXt"
##
## $heure_enq
## [1] "POSIXct" "POSIXt"
##
## $id_obs
## [1] "character"
##
## $id_sortie
## [1] "character"
##
## $inchiku
## [1] "character"
##
## $indienne
## [1] "character"
##
## $inf_pech_l
## [1] "character"
##
## $j
## [1] "character"
##
## $j3
## [1] "character"
##
## $j4
## [1] "character"
##
## $jigging
## [1] "character"
##
## $journee
## [1] "character"
##
## $joursin
## [1] "character"
##
## $lat
## [1] "character"
##
## $leur_surf
## [1] "character"
##
## $leurre_tt
## [1] "character"
##
## $ligne_m
## [1] "character"
##
## $loca_bat
## [1] "character"
##
## $loca_dom
## [1] "character"
##
## $longueur
## [1] "character"
##
## $m
## [1] "character"
##
## $m2
## [1] "character"
##
## $madai
## [1] "character"
##
## $matin
## [1] "character"
##
## $mod_peche
## [1] "character"
##
## $mode_eqt
## [1] "character"
##
## $mort_cru
## [1] "character"
##
## $mort_esp
## [1] "character"
##
## $mort_mll
## [1] "character"
##
## $mort_pss
## [1] "character"
##
## $mort_vers
## [1] "character"
##
## $motor
## [1] "character"
##
## $moursin
## [1] "character"
##
## $n
## [1] "character"
##
## $nasse
## [1] "character"
##
## $nb_ours
## [1] "character"
##
## $nb_pech_o
## [1] "character"
##
## $nb_pecheur
## [1] "numeric"
##
## $nb_sort_an
## [1] "character"
##
## $nb_sort_an6
## [1] "character"
##
## $nb_sous_tail
## [1] "character"
##
## $neb
## [1] "character"
##
## $nimp_q
## [1] "character"
##
## $niql
## [1] "character"
##
## $nom_asso
## [1] "character"
##
## $nom_esp_ind
## [1] "character"
##
## $nuit
## [1] "character"
##
## $o
## [1] "character"
##
## $obs
## [1] "character"
##
## $obs_stock_l
## [1] "character"
##
## $obs_stock_o
## [1] "character"
##
## $p_no_kill
## [1] "character"
##
## $palangre
## [1] "character"
##
## $palangro
## [1] "character"
##
## $pdb
## [1] "character"
##
## $pe
## [1] "numeric"
##
## $peche_cal
## [1] "character"
##
## $pelote
## [1] "character"
##
## $phase_lune
## [1] "character"
##
## $pierre
## [1] "character"
##
## $pierre_bd
## [1] "character"
##
## $po
## [1] "character"
##
## $port_atta
## [1] "character"
##
## $poss_bat
## [1] "character"
##
## $pour_jf
## [1] "character"
##
## $pourc_sem
## [1] "character"
##
## $pourc_we
## [1] "character"
##
## $prise_jour
## [1] "character"
##
## $procu_app
## [1] "character"
##
## $prof_m_moyen
## [1] "character"
##
## $proximite
## [1] "character"
##
## $q_esp
## [1] "character"
##
## $quot_max_o
## [1] "character"
##
## $raison_var
## [1] "character"
##
## $recommandation
## [1] "character"
##
## $reg_pech_l
## [1] "character"
##
## $reg_pech_o
## [1] "character"
##
## $res_alien
## [1] "character"
##
## $res_tour
## [1] "character"
##
## $rockfish
## [1] "character"
##
## $s
## [1] "character"
##
## $sais_pech_o
## [1] "character"
##
## $Saisie
## [1] "character"
##
## $secteur_po
## [1] "character"
##
## $secteur_po7
## [1] "character"
##
## $sem
## [1] "character"
##
## $sexe
## [1] "character"
##
## $shad
## [1] "character"
##
## $shore_jigg
## [1] "character"
##
## $soir
## [1] "character"
##
## $solu_gest
## [1] "character"
##
## $sondeur
## [1] "character"
##
## $sout_bd
## [1] "character"
##
## $surfcas
## [1] "character"
##
## $table_traçante
## [1] "character"
##
## $tail_min_o
## [1] "character"
##
## $temp
## [1] "character"
##
## $temps_parc
## [1] "character"
##
## $Temps_peche_effectif
## [1] "POSIXct" "POSIXt"
##
## $Temps_peche_estime
## [1] "POSIXct" "POSIXt"
##
## $tenya
## [1] "character"
##
## $tra_fond
## [1] "character"
##
## $tra_surf
## [1] "character"
##
## $tranquilite
## [1] "character"
##
## $turlutte
## [1] "character"
##
## $type_bat
## [1] "character"
##
## $vac
## [1] "character"
##
## $vire_ligne
## [1] "character"
##
## $viv_cru
## [1] "character"
##
## $viv_esp
## [1] "character"
##
## $viv_moll
## [1] "character"
##
## $viv_pss
## [1] "character"
##
## $viv_vers
## [1] "character"
##
## $vivier
## [1] "character"
##
## $we
## [1] "character"
##
## $x_degres
## [1] "character"
##
## $x_lon
## [1] "character"
##
## $x_lon_DD
## [1] "character"
##
## $x_min_dec
## [1] "character"
##
## $y_degres
## [1] "character"
##
## $y_lat
## [1] "character"
##
## $y_lat_DD
## [1] "character"
##
## $y_min_dec
## [1] "character"
##
## $z_1
## [1] "character"
##
## $z_2
## [1] "character"
##
## $z_3
## [1] "character"
##
## $z_4
## [1] "character"
##
## $z_54
## [1] "character"
##
## $z_55
## [1] "character"
##
## $z_56
## [1] "character"
##
## $z_57
## [1] "character"
##
## $z_58
## [1] "character"
##
## $z_59
## [1] "character"
##
## $z_6
## [1] "character"
##
## $z_60
## [1] "character"
##
## $z_61
## [1] "character"
##
## $z_7
## [1] "character"
##
## $z_8
## [1] "character"
##
## $z_9
## [1] "character"
##
## $zone_pro
## [1] "character"
# quid format hh:mm excel => imported as POSIXct ; if you want to force R to import it as character, it doen't work, so keep the automatic importation format.
head(survey$date) ; class(survey$date)
## [1] "44054" "44054" "44055" "44055" "44055" "44057"
## [1] "character"
head(survey$Temps_peche_effectif) ; class(survey$Temps_peche_effectif)
## [1] "1899-12-31 00:30:00 UTC" "1899-12-31 01:30:00 UTC"
## [3] "1899-12-31 00:30:00 UTC" "1899-12-31 04:30:00 UTC"
## [5] "1899-12-31 05:00:00 UTC" "1899-12-31 00:45:00 UTC"
## [1] "POSIXct" "POSIXt"
head(survey$h_debut) ; class(survey$h_debut)
## [1] "1899-12-31 07:00:00 UTC" "1899-12-31 06:30:00 UTC"
## [3] "1899-12-31 07:00:00 UTC" "1899-12-31 06:00:00 UTC"
## [5] "1899-12-31 06:00:00 UTC" "1899-12-31 10:00:00 UTC"
## [1] "POSIXct" "POSIXt"
unique(Meta.survey$Format)
## [1] "Binaire" "Texte" "Nombre" "Alphanumérique"
## [5] "Date" "Horaire" "-" "Réel"
Meta.survey$Format <- ifelse(Meta.survey$Format == "Binaire", "numeric", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "Texte", "character", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "Nombre", "character", Meta.survey$Format) #was numeric before, but some var supposed to be numric must be imported as character cfr e.g. age variable
Meta.survey$Format <- ifelse(Meta.survey$Format == "Alphanumérique", "character", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "Date", "date", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "Horaire", "POSIXct", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "-", "character", Meta.survey$Format)
Meta.survey$Format <- ifelse(Meta.survey$Format == "Réel", "character", Meta.survey$Format) #was numeric before, but some var supposed to be numric must be imported as character cfr age variable
unique(Meta.survey$Format)
## [1] "numeric" "character" "date" "POSIXct"
# issue with début & fin enquête var. importation
table(survey$deb_sortie)
##
## 0.2638888888888889 0.27083333333333331 0.29166666666666669 0.30208333333333331
## 2 19 63 1
## 0.3125 0.33333333333333331 0.34722222222222227 0.35416666666666669
## 41 54 33 73
## 0.36458333333333331 0.375 0.39583333333333331 0.41666666666666669
## 12 98 15 29
## 0.41666666666666702 0.4375 0.45833333333333331 0.46249999999999997
## 1 3 6 3
## 0.47916666666666669 0.54166666666666663 0.58333333333333337 0.625
## 1 5 12 11
## 0.66666666666666663 0.70833333333333337 0.72916666666666663 0.75
## 3 9 8 9
## 0.77083333333333337 0.79166666666666663 NA
## 4 4 72
survey$deb_sortie <- ifelse(survey$deb_sortie == "NA", NA, survey$deb_sortie)
table(survey$fin_sortie)
##
## 0.39583333333333331 0.41666666666666669 0.4375 0.45833333333333331
## 7 4 2 7
## 0.47569444444444442 0.47916666666666669 0.5 0.52083333333333337
## 1 6 40 18
## 0.54166666666666663 0.5625 0.58333333333333337 0.60416666666666663
## 38 22 97 22
## 0.625 0.64583333333333337 0.66666666666666663 0.6875
## 44 4 10 17
## 0.70833333333333337 0.72916666666666663 0.75 0.79166666666666663
## 64 13 32 38
## 0.8125 0.875 0.89583333333333337 0.91666666666666663
## 1 8 9 13
## NA
## 74
survey$fin_sortie <- ifelse(survey$fin_sortie == "NA", NA, survey$fin_sortie)
# transform them now in time format for below loop
survey$deb_sortie <- chron::times(as.numeric(survey$deb_sortie))
survey$fin_sortie <- chron::times(as.numeric(survey$fin_sortie))
survey$deb_sortie <- as.POSIXct(ifelse(is.na(survey$deb_sortie), NA, paste0("1899-12-31 ", as.character(survey$deb_sortie))))
survey$fin_sortie <- as.POSIXct(ifelse(is.na(survey$fin_sortie), NA, paste0("1899-12-31 ", as.character(survey$fin_sortie))))
intersect(unique(Meta.survey[,c("Libellé","Unité")])[["Libellé"]], unique(names(survey)))
## [1] "a" "abondance" "accessibilite" "act_peche"
## [5] "act_pro" "agachon" "age" "age_moyen"
## [9] "anc_posid" "aoursin" "apm" "assoc"
## [13] "aube" "autre" "autre_app" "autre_tech"
## [17] "avis_mes_l" "avis_mes_o" "avis_pnm" "bag_thon"
## [21] "broume" "cat_pro" "chas_trou" "co_pnmcca"
## [25] "code_insee" "comm_gest" "comm_rais_var" "commune"
## [29] "connaissance" "crepuscule" "csm" "d"
## [33] "date" "deb_age" "deb_sortie" "debarq"
## [37] "dep_csm" "dep_pdb" "dep_pe" "dep_po"
## [41] "direct_h" "direct_v" "doursin" "douz_jour"
## [45] "dur_moy_o" "dur_sort" "esp_cib" "esp_n_ind"
## [49] "espcib1" "espcib2" "espcib3" "etat_mer"
## [53] "f" "fiche_n" "fin_sortie" "fireball"
## [57] "flotteur" "fonds_rech" "force_v" "foursin"
## [61] "gps" "h_debut" "h_fin" "heure_enq"
## [65] "id_obs" "id_sortie" "inchiku" "indienne"
## [69] "inf_pech_l" "j" "jigging" "joursin"
## [73] "lat" "leur_surf" "leurre_tt" "ligne_m"
## [77] "loca_bat" "loca_dom" "longueur" "m"
## [81] "madai" "matin" "mod_peche" "mode_eqt"
## [85] "mort_cru" "mort_esp" "mort_mll" "mort_pss"
## [89] "mort_vers" "motor" "moursin" "n"
## [93] "nasse" "nb_ours" "nb_pech_o" "nb_pecheur"
## [97] "nb_sort_an" "nb_sous_tail" "neb" "nimp_q"
## [101] "niql" "nom_asso" "nom_esp_ind" "nuit"
## [105] "o" "obs" "obs_stock_l" "obs_stock_o"
## [109] "p_no_kill" "palangre" "palangro" "pdb"
## [113] "pe" "peche_cal" "pelote" "phase_lune"
## [117] "pierre" "pierre_bd" "po" "port_atta"
## [121] "poss_bat" "pour_jf" "pourc_sem" "pourc_we"
## [125] "prise_jour" "procu_app" "prof_m_moyen" "proximite"
## [129] "q_esp" "quot_max_o" "raison_var" "recommandation"
## [133] "reg_pech_l" "reg_pech_o" "res_alien" "res_tour"
## [137] "rockfish" "s" "sais_pech_o" "secteur_po"
## [141] "sem" "sexe" "shad" "shore_jigg"
## [145] "soir" "solu_gest" "sondeur" "sout_bd"
## [149] "surfcas" "table_traçante" "tail_min_o" "temp"
## [153] "temps_parc" "tenya" "tra_fond" "tra_surf"
## [157] "tranquilite" "turlutte" "type_bat" "vac"
## [161] "vire_ligne" "viv_cru" "viv_esp" "viv_moll"
## [165] "viv_pss" "viv_vers" "vivier" "we"
## [169] "x_lon" "x_lon_DD" "x_min_dec" "y_lat"
## [173] "y_lat_DD" "y_min_dec" "z_1" "z_2"
## [177] "z_3" "z_4" "z_54" "z_55"
## [181] "z_56" "z_57" "z_58" "z_59"
## [185] "z_6" "z_60" "z_61" "z_7"
## [189] "z_8" "z_9" "zone_pro"
length(unique(names(survey)))
## [1] 206
length(names(survey))
## [1] 206
survey[ , names(survey) %in% intersect(unique(Meta.survey[,c("Libellé","Unité")])[["Libellé"]], unique(names(survey)))]
## # A tibble: 770 × 191
## a abondance accessibilite act_peche act_pro agachon age age_moyen
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 0 0 1 cote_rocheuse Artisan(… 0 >50 50
## 2 0 0 1 cote_sableuse Cadres_e… 0 40-50 45
## 3 0 0 1 cote_sableuse Artisan(… 0 40-50 45
## 4 0 0 1 en_mer Employe(… 0 >50 50
## 5 0 0 1 en_mer Artisan(… 0 >50 50
## 6 0 1 1 en_mer Retraite… 0 >50 50
## 7 0 0 0 en_mer Cadres_e… 0 20-30 25
## 8 0 1 1 en_mer Artisan(… 0 >50 50
## 9 1 0 1 cote_rocheuse Sans_emp… 0 >50 50
## 10 0 0 1 cote_rocheuse Agricult… 0 >50 50
## # ℹ 760 more rows
## # ℹ 183 more variables: anc_posid <chr>, aoursin <chr>, apm <chr>, assoc <chr>,
## # aube <chr>, autre <chr>, autre_app <chr>, autre_tech <chr>,
## # avis_mes_l <chr>, avis_mes_o <chr>, avis_pnm <chr>, bag_thon <chr>,
## # broume <chr>, cat_pro <chr>, chas_trou <chr>, co_pnmcca <chr>,
## # code_insee <chr>, comm_gest <chr>, comm_rais_var <chr>, commune <chr>,
## # connaissance <chr>, crepuscule <chr>, csm <chr>, d <chr>, date <chr>, …
for (i in 1:length(survey)) {
#i=36
names(survey[,i])
typeof(unlist(survey[,i]))
fmt. <- unique(filter(Meta.survey, Libellé == names(survey[,i]))[["Format"]])
fmt. <- ifelse(length(fmt.) == 0, "null", fmt.)
if (fmt. == "date") {
survey[,i] <- as.Date(as.numeric(unlist(survey[,i])), origin = "1899-12-30", format = "%Y-%m-%d")
} else if (fmt. == "POSIXct") {
survey[,i] <- as.POSIXct(unlist(survey[,i]), origin = "1970-01-01 00:00:00", format = "%Y-%m-%d %H:%M:%S")
} else if (fmt. == "numeric") {
survey[,i] <- as.numeric(unlist(survey[,i]))
} else if (fmt. == "character") {
survey[,i] <- as.character(unlist(survey[,i]))
} else {
survey[,i]
}
rm(fmt.,i)
}
## Warning: NAs introduits lors de la conversion automatique
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## Warning in as.Date(as.numeric(unlist(survey[, i])), origin = "1899-12-30", :
## NAs introduits lors de la conversion automatique
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head(survey$date)
## [1] "2020-08-11" "2020-08-11" "2020-08-12" "2020-08-12" "2020-08-12"
## [6] "2020-08-14"
head(survey$Temps_peche_effectif) ; class(survey$Temps_peche_effectif)
## [1] "1899-12-31 00:30:00 UTC" "1899-12-31 01:30:00 UTC"
## [3] "1899-12-31 00:30:00 UTC" "1899-12-31 04:30:00 UTC"
## [5] "1899-12-31 05:00:00 UTC" "1899-12-31 00:45:00 UTC"
## [1] "POSIXct" "POSIXt"
head(survey$h_debut) ; class(survey$h_debut)
## h_debut1 h_debut2 h_debut3
## "1899-12-31 07:00:00 UTC" "1899-12-31 06:30:00 UTC" "1899-12-31 07:00:00 UTC"
## h_debut4 h_debut5 h_debut6
## "1899-12-31 06:00:00 UTC" "1899-12-31 06:00:00 UTC" "1899-12-31 10:00:00 UTC"
## [1] "POSIXct" "POSIXt"
setdiff(names(survey), Meta.survey$Libellé)
## [1] "a5" "autre10" "autre9"
## [4] "douz_jour8" "j3" "j4"
## [7] "journee" "m2" "nb_sort_an6"
## [10] "Saisie" "secteur_po7" "Temps_peche_effectif"
## [13] "Temps_peche_estime" "x_degres" "y_degres"
survey[,setdiff(names(survey), Meta.survey$Libellé)[[1]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[1]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[2]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[2]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[3]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[3]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[4]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[4]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[5]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[5]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[6]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[6]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[7]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[7]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[8]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[8]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[9]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[9]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[10]]] <- as.character(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[10]]]))
survey[,setdiff(names(survey), Meta.survey$Libellé)[[11]]] <- as.character(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[11]]]))
# the two variables "Temps_peche_effectif" & "Temps_peche_estime" were automatically imported as POSIXct variable so don't change anything here
#survey[,setdiff(names(survey), Meta.survey$Libellé)[[12]]] <- as.POSIXct(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[12]]]), origin = "19700-01-01 00:00:00", format = "%Y-%m-%d %H:%M:%S")
#survey[,setdiff(names(survey), Meta.survey$Libellé)[[13]]] <- as.POSIXct(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[13]]]), origin = "1970-01-01 00:00:00", format = "%Y-%m-%d %H:%M:%S")
survey[,setdiff(names(survey), Meta.survey$Libellé)[[14]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[14]]]))
## Warning: NAs introduits lors de la conversion automatique
survey[,setdiff(names(survey), Meta.survey$Libellé)[[15]]] <- as.numeric(unlist(survey[,setdiff(names(survey), Meta.survey$Libellé)[[15]]]))
## Warning: NAs introduits lors de la conversion automatique
unique(survey$h_debut) ; survey$h_debut <- as_hms(survey$h_debut)
## [1] "1899-12-31 07:00:00 UTC" "1899-12-31 06:30:00 UTC"
## [3] "1899-12-31 06:00:00 UTC" "1899-12-31 10:00:00 UTC"
## [5] "1899-12-31 05:30:00 UTC" "1899-12-31 07:30:00 UTC"
## [7] "1899-12-31 08:00:00 UTC" "1899-12-31 19:30:00 UTC"
## [9] "1899-12-31 18:00:00 UTC" "1899-12-31 20:00:00 UTC"
## [11] "1899-12-31 08:30:00 UTC" "1899-12-31 09:30:00 UTC"
## [13] "1899-12-31 09:00:00 UTC" "1899-12-31 19:00:00 UTC"
## [15] "1899-12-31 17:00:00 UTC" "1899-12-31 09:25:00 UTC"
## [17] "1899-12-31 17:30:00 UTC" "1899-12-31 10:20:00 UTC"
## [19] "1899-12-31 10:30:00 UTC" "1899-12-31 05:00:00 UTC"
## [21] "1899-12-31 08:58:00 UTC" "1899-12-31 06:10:00 UTC"
## [23] "1899-12-31 15:00:00 UTC" "1899-12-31 07:10:00 UTC"
## [25] "1899-12-31 06:15:00 UTC" "1899-12-31 12:00:00 UTC"
## [27] "1899-12-31 04:45:00 UTC" "1899-12-31 12:30:00 UTC"
## [29] "1899-12-31 10:45:00 UTC" "1899-12-31 13:00:00 UTC"
## [31] "1899-12-31 14:00:00 UTC" "1899-12-31 08:15:00 UTC"
## [33] "1899-12-31 09:24:00 UTC" "1899-12-31 14:30:00 UTC"
## [35] "1899-12-31 15:30:00 UTC" "1899-12-31 16:00:00 UTC"
## [37] "1899-12-31 09:15:00 UTC" "1899-12-31 11:00:00 UTC"
## [39] "1899-12-31 09:40:00 UTC" "1899-12-31 10:59:00 UTC"
## [41] "1899-12-31 04:00:00 UTC" "1899-12-31 09:05:00 UTC"
## [43] "1899-12-31 07:20:00 UTC" "1899-12-31 06:50:00 UTC"
## [45] "1899-12-31 06:40:00 UTC" "1899-12-31 00:00:00 UTC"
## [47] "1899-12-31 08:45:00 UTC" "1899-12-31 11:45:00 UTC"
## [49] "1899-12-31 07:45:00 UTC" "1899-12-31 03:00:00 UTC"
## [51] "1899-12-31 13:30:00 UTC" "1899-12-31 16:15:00 UTC"
## [53] "1899-12-31 09:45:00 UTC" "1899-12-31 11:30:00 UTC"
## [55] "1899-12-31 16:30:00 UTC" "1899-12-31 18:10:00 UTC"
## [57] "1899-12-31 15:45:00 UTC" "1899-12-31 10:10:00 UTC"
## [59] "1899-12-31 09:10:00 UTC" "1899-12-31 12:10:00 UTC"
## [61] "1899-12-31 15:15:00 UTC" NA
unique(survey$h_fin) ; survey$h_fin <- as_hms(survey$h_fin)
## [1] "1899-12-31 09:00:00 UTC" "1899-12-31 08:30:00 UTC"
## [3] "1899-12-31 10:00:00 UTC" "1899-12-31 10:30:00 UTC"
## [5] "1899-12-31 11:30:00 UTC" "1899-12-31 12:00:00 UTC"
## [7] "1899-12-31 09:30:00 UTC" "1899-12-31 21:30:00 UTC"
## [9] "1899-12-31 20:00:00 UTC" "1899-12-31 22:00:00 UTC"
## [11] "1899-12-31 23:00:00 UTC" "1899-12-31 08:00:00 UTC"
## [13] "1899-12-31 19:30:00 UTC" "1899-12-31 21:00:00 UTC"
## [15] "1899-12-31 11:00:00 UTC" "1899-12-31 15:00:00 UTC"
## [17] "1899-12-31 19:00:00 UTC" "1899-12-31 14:00:00 UTC"
## [19] "1899-12-31 17:00:00 UTC" "1899-12-31 16:00:00 UTC"
## [21] "1899-12-31 18:00:00 UTC" "1899-12-31 16:30:00 UTC"
## [23] "1899-12-31 09:15:00 UTC" "1899-12-31 13:15:00 UTC"
## [25] "1899-12-31 12:20:00 UTC" "1899-12-31 10:40:00 UTC"
## [27] "1899-12-31 17:30:00 UTC" "1899-12-31 12:30:00 UTC"
## [29] "1899-12-31 13:00:00 UTC" "1899-12-31 13:30:00 UTC"
## [31] "1899-12-31 10:45:00 UTC" "1899-12-31 10:15:00 UTC"
## [33] "1899-12-31 09:45:00 UTC" "1899-12-31 20:30:00 UTC"
## [35] "1899-12-31 11:15:00 UTC" "1899-12-31 11:45:00 UTC"
## [37] "1900-01-01 00:00:00 UTC" "1899-12-31 15:30:00 UTC"
## [39] "1899-12-31 16:15:00 UTC" "1899-12-31 09:50:00 UTC"
## [41] "1899-12-31 11:20:00 UTC" "1899-12-31 18:30:00 UTC"
## [43] "1899-12-31 11:40:00 UTC" "1899-12-31 10:50:00 UTC"
## [45] "1899-12-31 10:10:00 UTC" "1899-12-31 17:10:00 UTC"
## [47] "1899-12-31 17:20:00 UTC" "1899-12-31 18:05:00 UTC"
## [49] "1899-12-31 18:15:00 UTC" "1899-12-31 11:10:00 UTC"
## [51] NA
unique(survey$heure_enq) ; survey$heure_enq <- as_hms(survey$heure_enq)
## [1] "1899-12-31 07:30:00 UTC" "1899-12-31 08:00:00 UTC"
## [3] "1899-12-31 10:30:00 UTC" "1899-12-31 11:00:00 UTC"
## [5] "1899-12-31 10:45:00 UTC" "1899-12-31 11:05:00 UTC"
## [7] "1899-12-31 11:25:00 UTC" "1899-12-31 07:15:00 UTC"
## [9] "1899-12-31 08:15:00 UTC" "1899-12-31 19:45:00 UTC"
## [11] "1899-12-31 20:15:00 UTC" "1899-12-31 20:50:00 UTC"
## [13] "1899-12-31 21:00:00 UTC" "1899-12-31 07:40:00 UTC"
## [15] "1899-12-31 08:40:00 UTC" "1899-12-31 08:45:00 UTC"
## [17] "1899-12-31 09:05:00 UTC" "1899-12-31 09:50:00 UTC"
## [19] "1899-12-31 11:30:00 UTC" "1899-12-31 07:50:00 UTC"
## [21] "1899-12-31 08:05:00 UTC" "1899-12-31 08:30:00 UTC"
## [23] "1899-12-31 09:30:00 UTC" "1899-12-31 07:05:00 UTC"
## [25] "1899-12-31 09:00:00 UTC" "1899-12-31 10:15:00 UTC"
## [27] "1899-12-31 10:50:00 UTC" "1899-12-31 07:00:00 UTC"
## [29] "1899-12-31 07:35:00 UTC" "1899-12-31 07:55:00 UTC"
## [31] "1899-12-31 10:20:00 UTC" "1899-12-31 19:05:00 UTC"
## [33] "1899-12-31 19:40:00 UTC" "1899-12-31 19:50:00 UTC"
## [35] "1899-12-31 20:10:00 UTC" "1899-12-31 09:25:00 UTC"
## [37] "1899-12-31 09:55:00 UTC" "1899-12-31 18:45:00 UTC"
## [39] "1899-12-31 19:10:00 UTC" "1899-12-31 19:30:00 UTC"
## [41] "1899-12-31 20:00:00 UTC" "1899-12-31 09:15:00 UTC"
## [43] "1899-12-31 19:15:00 UTC" "1899-12-31 19:35:00 UTC"
## [45] "1899-12-31 10:05:00 UTC" "1899-12-31 10:35:00 UTC"
## [47] "1899-12-31 09:45:00 UTC" "1899-12-31 13:15:00 UTC"
## [49] "1899-12-31 13:40:00 UTC" "1899-12-31 17:40:00 UTC"
## [51] "1899-12-31 18:00:00 UTC" "1899-12-31 18:30:00 UTC"
## [53] "1899-12-31 18:55:00 UTC" "1899-12-31 20:20:00 UTC"
## [55] "1899-12-31 12:25:00 UTC" "1899-12-31 08:50:00 UTC"
## [57] "1899-12-31 09:20:00 UTC" "1899-12-31 08:10:00 UTC"
## [59] "1899-12-31 10:17:00 UTC" "1899-12-31 12:00:00 UTC"
## [61] "1899-12-31 12:17:00 UTC" "1899-12-31 12:38:00 UTC"
## [63] "1899-12-31 12:56:00 UTC" "1899-12-31 09:57:00 UTC"
## [65] "1899-12-31 09:10:00 UTC" "1899-12-31 10:21:00 UTC"
## [67] "1899-12-31 11:50:00 UTC" "1899-12-31 11:57:00 UTC"
## [69] "1899-12-31 11:01:00 UTC" "1899-12-31 10:02:00 UTC"
## [71] "1899-12-31 11:38:00 UTC" "1899-12-31 09:40:00 UTC"
## [73] "1899-12-31 09:21:00 UTC" "1899-12-31 16:00:00 UTC"
## [75] "1899-12-31 09:51:00 UTC" "1899-12-31 10:08:00 UTC"
## [77] "1899-12-31 10:18:00 UTC" "1899-12-31 10:49:00 UTC"
## [79] "1899-12-31 12:16:00 UTC" "1899-12-31 11:18:00 UTC"
## [81] "1899-12-31 12:02:00 UTC" "1899-12-31 08:11:00 UTC"
## [83] "1899-12-31 08:35:00 UTC" "1899-12-31 11:23:00 UTC"
## [85] "1899-12-31 09:38:00 UTC" "1899-12-31 11:12:00 UTC"
## [87] "1899-12-31 11:45:00 UTC" "1899-12-31 09:47:00 UTC"
## [89] "1899-12-31 10:00:00 UTC" "1899-12-31 10:23:00 UTC"
## [91] "1899-12-31 11:03:00 UTC" "1899-12-31 11:48:00 UTC"
## [93] "1899-12-31 10:26:00 UTC" "1899-12-31 15:23:00 UTC"
## [95] "1899-12-31 15:55:00 UTC" "1899-12-31 09:13:00 UTC"
## [97] "1899-12-31 07:53:00 UTC" "1899-12-31 09:52:00 UTC"
## [99] "1899-12-31 17:45:00 UTC" "1899-12-31 07:10:00 UTC"
## [101] "1899-12-31 07:45:00 UTC" "1899-12-31 10:10:00 UTC"
## [103] "1899-12-31 09:06:00 UTC" "1899-12-31 08:49:00 UTC"
## [105] "1899-12-31 07:02:00 UTC" "1899-12-31 07:34:00 UTC"
## [107] "1899-12-31 13:00:00 UTC" "1899-12-31 11:26:00 UTC"
## [109] "1899-12-31 10:40:00 UTC" "1899-12-31 12:27:00 UTC"
## [111] "1899-12-31 15:30:00 UTC" "1899-12-31 16:15:00 UTC"
## [113] "1899-12-31 10:39:00 UTC" "1899-12-31 10:46:00 UTC"
## [115] "1899-12-31 11:19:00 UTC" "1899-12-31 11:13:00 UTC"
## [117] "1899-12-31 08:59:00 UTC" "1899-12-31 10:57:00 UTC"
## [119] "1899-12-31 16:30:00 UTC" "1899-12-31 16:45:00 UTC"
## [121] "1899-12-31 09:54:00 UTC" "1899-12-31 11:07:00 UTC"
## [123] "1899-12-31 11:37:00 UTC" "1899-12-31 11:49:00 UTC"
## [125] "1899-12-31 12:53:00 UTC" "1899-12-31 13:45:00 UTC"
## [127] "1899-12-31 14:10:00 UTC" "1899-12-31 11:39:00 UTC"
## [129] "1899-12-31 11:40:00 UTC" "1899-12-31 12:20:00 UTC"
## [131] "1899-12-31 09:35:00 UTC" "1899-12-31 13:43:00 UTC"
## [133] "1899-12-31 10:43:00 UTC" "1899-12-31 11:58:00 UTC"
## [135] "1899-12-31 14:15:00 UTC" "1899-12-31 14:36:00 UTC"
## [137] "1899-12-31 07:21:00 UTC" "1899-12-31 13:59:00 UTC"
## [139] "1899-12-31 07:24:00 UTC" "1899-12-31 07:37:00 UTC"
## [141] "1899-12-31 09:16:00 UTC" "1899-12-31 10:06:00 UTC"
## [143] "1899-12-31 10:25:00 UTC" "1899-12-31 10:54:00 UTC"
## [145] "1899-12-31 11:09:00 UTC" "1899-12-31 10:37:00 UTC"
## [147] "1899-12-31 11:15:00 UTC" "1899-12-31 11:35:00 UTC"
## [149] "1899-12-31 08:52:00 UTC" "1899-12-31 10:04:00 UTC"
## [151] "1899-12-31 11:47:00 UTC" "1899-12-31 12:12:00 UTC"
## [153] "1899-12-31 12:40:00 UTC" "1899-12-31 10:28:00 UTC"
## [155] "1899-12-31 12:09:00 UTC" "1899-12-31 12:28:00 UTC"
## [157] "1899-12-31 12:07:00 UTC" "1899-12-31 12:15:00 UTC"
## [159] "1899-12-31 15:00:00 UTC" "1899-12-31 12:10:00 UTC"
## [161] "1899-12-31 14:45:00 UTC" "1899-12-31 16:20:00 UTC"
## [163] "1899-12-31 12:30:00 UTC" "1899-12-31 11:20:00 UTC"
## [165] "1899-12-31 15:40:00 UTC" "1899-12-31 14:50:00 UTC"
## [167] "1899-12-31 12:45:00 UTC" "1899-12-31 14:30:00 UTC"
## [169] "1899-12-31 13:30:00 UTC" "1899-12-31 17:00:00 UTC"
## [171] "1899-12-31 14:00:00 UTC" "1899-12-31 14:20:00 UTC"
## [173] "1899-12-31 14:40:00 UTC" "1899-12-31 15:50:00 UTC"
## [175] "1899-12-31 15:10:00 UTC" "1899-12-31 15:45:00 UTC"
## [177] "1899-12-31 16:40:00 UTC" "1899-12-31 16:50:00 UTC"
## [179] "1899-12-31 17:10:00 UTC" "1899-12-31 17:20:00 UTC"
## [181] "1899-12-31 17:30:00 UTC" "1899-12-31 18:05:00 UTC"
## [183] "1899-12-31 18:10:00 UTC" "1899-12-31 18:15:00 UTC"
## [185] "1899-12-31 18:20:00 UTC" "1899-12-31 21:30:00 UTC"
## [187] "1899-12-31 16:10:00 UTC" "1899-12-31 11:10:00 UTC"
## [189] NA
unique(survey$Temps_peche_estime) ; survey$Temps_peche_estime <- as_hms(survey$Temps_peche_estime)
## [1] "1899-12-31 02:00:00 UTC" "1899-12-31 01:30:00 UTC"
## [3] "1899-12-31 04:00:00 UTC" "1899-12-31 04:30:00 UTC"
## [5] "1899-12-31 05:00:00 UTC" "1899-12-31 03:30:00 UTC"
## [7] "1899-12-31 01:00:00 UTC" "1899-12-31 03:00:00 UTC"
## [9] "1899-12-31 02:30:00 UTC" "1899-12-31 06:30:00 UTC"
## [11] "1899-12-31 05:30:00 UTC" "1899-12-31 02:35:00 UTC"
## [13] "1899-12-31 01:40:00 UTC" "1899-12-31 07:00:00 UTC"
## [15] "1899-12-31 08:00:00 UTC" "1899-12-31 09:30:00 UTC"
## [17] "1899-12-31 06:00:00 UTC" "1899-12-31 03:02:00 UTC"
## [19] "1899-12-31 05:50:00 UTC" "1899-12-31 09:00:00 UTC"
## [21] "1899-12-31 11:00:00 UTC" "1899-12-31 10:00:00 UTC"
## [23] "1899-12-31 08:30:00 UTC" "1899-12-31 13:00:00 UTC"
## [25] "1899-12-31 02:20:00 UTC" "1899-12-31 07:15:00 UTC"
## [27] "1899-12-31 00:45:00 UTC" "1899-12-31 01:35:00 UTC"
## [29] "1899-12-31 01:10:00 UTC" "1899-12-31 03:45:00 UTC"
## [31] "1899-12-31 03:36:00 UTC" "1899-12-31 02:15:00 UTC"
## [33] "1899-12-31 01:05:00 UTC" "1899-12-31 02:01:00 UTC"
## [35] "1899-12-31 04:15:00 UTC" "1899-12-31 07:55:00 UTC"
## [37] "1899-12-31 00:30:00 UTC" "1899-12-31 02:45:00 UTC"
## [39] "1899-12-31 04:10:00 UTC" "1899-12-31 03:20:00 UTC"
## [41] "1899-12-31 12:00:00 UTC" "1899-12-31 07:30:00 UTC"
## [43] "1899-12-31 15:00:00 UTC" "1899-12-31 03:15:00 UTC"
## [45] "1899-12-31 08:15:00 UTC" "1899-12-31 04:45:00 UTC"
## [47] "1899-12-31 18:30:00 UTC" "1899-12-31 01:45:00 UTC"
## [49] "1899-12-31 02:50:00 UTC" "1899-12-31 03:50:00 UTC"
## [51] "1899-12-31 02:40:00 UTC" "1899-12-31 00:40:00 UTC"
## [53] "1899-12-31 17:00:00 UTC" "1899-12-31 02:10:00 UTC"
## [55] "1899-12-31 08:10:00 UTC" "1899-12-31 00:50:00 UTC"
## [57] "1899-12-31 04:50:00 UTC" "1899-12-31 00:00:00 UTC"
## [59] NA
unique(survey$Temps_peche_effectif) ; survey$Temps_peche_effectif <- as_hms(survey$Temps_peche_effectif)
## [1] "1899-12-31 00:30:00 UTC" "1899-12-31 01:30:00 UTC"
## [3] "1899-12-31 04:30:00 UTC" "1899-12-31 05:00:00 UTC"
## [5] "1899-12-31 00:45:00 UTC" "1899-12-31 01:05:00 UTC"
## [7] "1899-12-31 04:25:00 UTC" "1899-12-31 01:45:00 UTC"
## [9] "1899-12-31 00:00:00 UTC" "1899-12-31 00:15:00 UTC"
## [11] "1899-12-31 02:15:00 UTC" "1899-12-31 00:50:00 UTC"
## [13] "1899-12-31 01:00:00 UTC" "1899-12-31 01:40:00 UTC"
## [15] "1899-12-31 02:40:00 UTC" "1899-12-31 02:05:00 UTC"
## [17] "1899-12-31 01:20:00 UTC" "1899-12-31 02:00:00 UTC"
## [19] "1899-12-31 03:00:00 UTC" "1899-12-31 01:50:00 UTC"
## [21] "1899-12-31 01:35:00 UTC" "1899-12-31 01:55:00 UTC"
## [23] "1899-12-31 04:20:00 UTC" "1899-12-31 00:05:00 UTC"
## [25] "1899-12-31 01:10:00 UTC" "1899-12-31 03:25:00 UTC"
## [27] "1899-12-31 04:00:00 UTC" "1899-12-31 02:45:00 UTC"
## [29] "1899-12-31 02:10:00 UTC" "1899-12-31 01:15:00 UTC"
## [31] "1899-12-31 03:15:00 UTC" "1899-12-31 00:40:00 UTC"
## [33] "1899-12-31 04:05:00 UTC" "1899-12-31 03:20:00 UTC"
## [35] "1899-12-31 03:35:00 UTC" "1899-12-31 03:30:00 UTC"
## [37] "1899-12-31 04:40:00 UTC" "1899-12-31 00:10:00 UTC"
## [39] "1899-12-31 00:20:00 UTC" "1899-12-31 01:17:00 UTC"
## [41] "1899-12-31 05:35:00 UTC" "1899-12-31 05:17:00 UTC"
## [43] "1899-12-31 04:38:00 UTC" "1899-12-31 05:26:00 UTC"
## [45] "1899-12-31 03:57:00 UTC" "1899-12-31 03:21:00 UTC"
## [47] "1899-12-31 04:57:00 UTC" "1899-12-31 00:02:00 UTC"
## [49] "1899-12-31 02:01:00 UTC" "1899-12-31 01:02:00 UTC"
## [51] "1899-12-31 04:10:00 UTC" "1899-12-31 05:08:00 UTC"
## [53] "1899-12-31 08:00:00 UTC" "1899-12-31 03:51:00 UTC"
## [55] "1899-12-31 01:38:00 UTC" "1899-12-31 03:18:00 UTC"
## [57] "1899-12-31 04:49:00 UTC" "1899-12-31 02:46:00 UTC"
## [59] "1899-12-31 05:02:00 UTC" "1899-12-31 00:11:00 UTC"
## [61] "1899-12-31 04:23:00 UTC" "1899-12-31 01:51:00 UTC"
## [63] "1899-12-31 03:38:00 UTC" "1899-12-31 01:12:00 UTC"
## [65] "1899-12-31 03:45:00 UTC" "1899-12-31 01:47:00 UTC"
## [67] "1899-12-31 02:23:00 UTC" "1899-12-31 00:33:00 UTC"
## [69] "1899-12-31 04:18:00 UTC" "1899-12-31 03:26:00 UTC"
## [71] "1899-12-31 02:02:00 UTC" "1899-12-31 00:55:00 UTC"
## [73] "1899-12-31 00:23:00 UTC" "1899-12-31 02:38:00 UTC"
## [75] "1899-12-31 01:13:00 UTC" "1899-12-31 01:53:00 UTC"
## [77] "1899-12-31 04:22:00 UTC" "1899-12-31 02:06:00 UTC"
## [79] "1899-12-31 01:19:00 UTC" "1899-12-31 01:04:00 UTC"
## [81] "1899-12-31 01:49:00 UTC" "1899-12-31 02:20:00 UTC"
## [83] "1899-12-31 06:41:00 UTC" "1899-12-31 03:50:00 UTC"
## [85] "1899-12-31 01:42:00 UTC" "1899-12-31 02:30:00 UTC"
## [87] "1899-12-31 04:53:00 UTC" "1899-12-31 03:39:00 UTC"
## [89] "1899-12-31 02:03:00 UTC" "1899-12-31 01:46:00 UTC"
## [91] "1899-12-31 04:19:00 UTC" "1899-12-31 00:21:00 UTC"
## [93] "1899-12-31 00:59:00 UTC" "1899-12-31 03:27:00 UTC"
## [95] "1899-12-31 01:08:00 UTC" "1899-12-31 02:24:00 UTC"
## [97] "1899-12-31 01:52:00 UTC" "1899-12-31 01:37:00 UTC"
## [99] "1899-12-31 02:53:00 UTC" "1899-12-31 05:10:00 UTC"
## [101] "1899-12-31 00:01:00 UTC" "1899-12-31 01:39:00 UTC"
## [103] "1899-12-31 02:50:00 UTC" "1899-12-31 02:35:00 UTC"
## [105] "1899-12-31 03:43:00 UTC" "1899-12-31 03:54:00 UTC"
## [107] "1899-12-31 01:43:00 UTC" "1899-12-31 04:58:00 UTC"
## [109] "1899-12-31 05:15:00 UTC" "1899-12-31 06:30:00 UTC"
## [111] "1899-12-31 07:36:00 UTC" "1899-12-31 06:59:00 UTC"
## [113] "1899-12-31 00:54:00 UTC" "1899-12-31 09:00:00 UTC"
## [115] "1899-12-31 02:51:00 UTC" "1899-12-31 01:54:00 UTC"
## [117] "1899-12-31 04:39:00 UTC" "1899-12-31 02:37:00 UTC"
## [119] "1899-12-31 04:35:00 UTC" "1899-12-31 00:07:00 UTC"
## [121] "1899-12-31 03:13:00 UTC" "1899-12-31 04:04:00 UTC"
## [123] "1899-12-31 05:12:00 UTC" "1899-12-31 06:20:00 UTC"
## [125] "1899-12-31 05:40:00 UTC" "1899-12-31 00:58:00 UTC"
## [127] "1899-12-31 01:09:00 UTC" "1899-12-31 01:28:00 UTC"
## [129] "1899-12-31 02:16:00 UTC" "1899-12-31 06:10:00 UTC"
## [131] "1899-12-31 06:45:00 UTC" "1899-12-31 10:00:00 UTC"
## [133] "1899-12-31 05:30:00 UTC" "1899-12-31 07:30:00 UTC"
## [135] "1899-12-31 06:00:00 UTC" "1899-12-31 08:10:00 UTC"
## [137] "1899-12-31 00:35:00 UTC" NA
unique(survey$deb_sortie) ; survey$deb_sortie <- as_hms(survey$deb_sortie)
## [1] "1899-12-31 07:00:00 UTC" "1899-12-31 19:00:00 UTC"
## [3] "1899-12-31 18:30:00 UTC" "1899-12-31 07:30:00 UTC"
## [5] "1899-12-31 18:00:00 UTC" "1899-12-31 06:30:00 UTC"
## [7] "1899-12-31 08:30:00 UTC" "1899-12-31 08:00:00 UTC"
## [9] "1899-12-31 17:30:00 UTC" "1899-12-31 09:00:00 UTC"
## [11] "1899-12-31 09:30:00 UTC" "1899-12-31 08:45:00 UTC"
## [13] "1899-12-31 17:00:00 UTC" "1899-12-31 10:00:00 UTC"
## [15] "1899-12-31 06:20:00 UTC" "1899-12-31 07:15:00 UTC"
## [17] "1899-12-31 11:06:00 UTC" "1899-12-31 15:00:00 UTC"
## [19] "1899-12-31 13:00:00 UTC" "1899-12-31 11:00:00 UTC"
## [21] "1899-12-31 11:30:00 UTC" "1899-12-31 14:00:00 UTC"
## [23] "1899-12-31 16:00:00 UTC" "1899-12-31 08:20:00 UTC"
## [25] "1899-12-31 10:30:00 UTC" NA
unique(survey$fin_sortie) ; survey$fin_sortie <- as_hms(survey$fin_sortie)
## [1] "1899-12-31 13:00:00 UTC" "1899-12-31 14:00:00 UTC"
## [3] "1899-12-31 22:00:00 UTC" "1899-12-31 12:00:00 UTC"
## [5] "1899-12-31 21:30:00 UTC" "1899-12-31 11:00:00 UTC"
## [7] "1899-12-31 12:30:00 UTC" "1899-12-31 21:00:00 UTC"
## [9] "1899-12-31 14:30:00 UTC" "1899-12-31 10:30:00 UTC"
## [11] "1899-12-31 11:30:00 UTC" "1899-12-31 13:30:00 UTC"
## [13] "1899-12-31 11:25:00 UTC" "1899-12-31 09:30:00 UTC"
## [15] "1899-12-31 19:30:00 UTC" "1899-12-31 10:00:00 UTC"
## [17] "1899-12-31 15:00:00 UTC" "1899-12-31 17:30:00 UTC"
## [19] "1899-12-31 17:00:00 UTC" "1899-12-31 16:30:00 UTC"
## [21] "1899-12-31 18:00:00 UTC" NA
## [23] "1899-12-31 15:30:00 UTC" "1899-12-31 16:00:00 UTC"
## [25] "1899-12-31 19:00:00 UTC"
head(survey$date) ; class(survey$date)
## [1] "2020-08-11" "2020-08-11" "2020-08-12" "2020-08-12" "2020-08-12"
## [6] "2020-08-14"
## [1] "Date"
head(survey$Temps_peche_effectif) ; class(survey$Temps_peche_effectif)
## 00:30:00
## 01:30:00
## 00:30:00
## 04:30:00
## 05:00:00
## 00:45:00
## [1] "hms" "difftime"
head(survey$h_debut) ; class(survey$h_debut)
## 07:00:00
## 06:30:00
## 07:00:00
## 06:00:00
## 06:00:00
## 10:00:00
## [1] "hms" "difftime"
Meta.survey <- read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "Metha_enquete_terrain_publique", col_names = T, range = "A14:D218")
Meta.survey$Libellé
## [1] "mode_eqt" "fiche_n" "id_sortie"
## [4] "id_obs" "date" "heure_enq"
## [7] "lat" "y_lat" "y_degre"
## [10] "y_min_dec" "y_lat_DD" "x_lon"
## [13] "x_degre" "x_min_dec" "x_lon_DD"
## [16] "etat_mer" "temp" "neb"
## [19] "force_v" "direct_v" "direct_h"
## [22] "phase_lune" "deb_sortie" "fin_sortie"
## [25] "mod_peche" "prof_m" "prof_m_moyen"
## [28] "nb_pecheur" "obs" "act_peche"
## [31] "debarq" "sexe" "age"
## [34] "age_moyen" "cat_pro" "act_pro"
## [37] "commune" "code_insee" "res_tour"
## [40] "assoc" "nom_asso" "pdb"
## [43] "csm" "pe" "po"
## [46] "deb_age" "temps_parc" "nb_sort_an"
## [49] "j" "f" "m"
## [52] "a" "m" "j"
## [55] "j" "a" "s"
## [58] "o" "n" "d"
## [61] "niql" "vac" "we"
## [64] "sem" "aube" "matin"
## [67] "soir" "crepuscule" "nuit"
## [70] "apm" "journée" "nimp_q"
## [73] "espcib1" "espcib2" "espcib3"
## [76] "p_no_kill" "bag_thon" "z_1"
## [79] "z_2" "z_3" "z_4"
## [82] "z_6" "z_7" "z_8"
## [85] "z_9" "z_54" "z_55"
## [88] "z_56" "z_57" "z_58"
## [91] "z_59" "z_60" "z_61"
## [94] "doursin" "joursin" "foursin"
## [97] "moursin" "aoursin" "pourc_sem"
## [100] "pourc_we" "pour_jf" "nb_sort_an"
## [103] "dur_sort" "secteur_po" "douz_jour"
## [106] "nb_pech_o" "dur_moy_o" "nb_ours"
## [109] "nb_sous_tail" "poss_bat" "type_bat"
## [112] "motor" "longueur" "loca_bat"
## [115] "loca_dom" "port_atta" "gps"
## [118] "sondeur" "vivier" "table_traçante"
## [121] "vire_ligne" "autre" "anc_posid"
## [124] "dep_pdb" "dep_pe" "dep_csm"
## [127] "dep_po" "co_pnmcca" "zone_pro"
## [130] "reg_pech_l" "reg_pech_o" "sais_pech_o"
## [133] "tail_min_o" "quot_max_o" "inf_pech_l"
## [136] "avis_mes_l" "avis_mes_o" "obs_stock_o"
## [139] "obs_stock_l" "q_esp" "raison_var"
## [142] "comm_rais_var" "solu_gest" "comm_gest"
## [145] "esp_n_ind" "nom_esp_ind" "res_alien"
## [148] "avis_pnm" "h_debut" "h_fin"
## [151] "temps_pêche" "temps_peche_estime" "accessibilite"
## [154] "proximite" "connaissance" "recommandation"
## [157] "autre" "abondance" "tranquilite"
## [160] "fonds_rech" "esp_cib" "mort_pss"
## [163] "mort_cru" "mort_mll" "mort_vers"
## [166] "mort_esp" "viv_vers" "viv_pss"
## [169] "viv_cru" "viv_moll" "autre"
## [172] "viv_esp" "autre_app" "procu_app"
## [175] "agachon" "indienne" "chas_trou"
## [178] "tra_fond" "tra_surf" "pierre"
## [181] "palangro" "palangre" "nasse"
## [184] "ligne_m" "broume" "flotteur"
## [187] "peche_cal" "surfcas" "pelote"
## [190] "pierre_bd" "sout_bd" "leurre_tt"
## [193] "turlutte" "leur_surf" "rockfish"
## [196] "shad" "shore_jigg" "jigging"
## [199] "tenya" "madai" "inchiku"
## [202] "fireball" "autre_tech" "prise_jour"
union(names(survey),Meta.survey$Libellé)
## [1] "a" "a5" "abondance"
## [4] "accessibilite" "act_peche" "act_pro"
## [7] "agachon" "age" "age_moyen"
## [10] "anc_posid" "aoursin" "apm"
## [13] "assoc" "aube" "autre"
## [16] "autre_app" "autre_tech" "autre10"
## [19] "autre9" "avis_mes_l" "avis_mes_o"
## [22] "avis_pnm" "bag_thon" "broume"
## [25] "cat_pro" "chas_trou" "co_pnmcca"
## [28] "code_insee" "comm_gest" "comm_rais_var"
## [31] "commune" "connaissance" "crepuscule"
## [34] "csm" "d" "date"
## [37] "deb_age" "deb_sortie" "debarq"
## [40] "dep_csm" "dep_pdb" "dep_pe"
## [43] "dep_po" "direct_h" "direct_v"
## [46] "doursin" "douz_jour" "douz_jour8"
## [49] "dur_moy_o" "dur_sort" "esp_cib"
## [52] "esp_n_ind" "espcib1" "espcib2"
## [55] "espcib3" "etat_mer" "f"
## [58] "fiche_n" "fin_sortie" "fireball"
## [61] "flotteur" "fonds_rech" "force_v"
## [64] "foursin" "gps" "h_debut"
## [67] "h_fin" "heure_enq" "id_obs"
## [70] "id_sortie" "inchiku" "indienne"
## [73] "inf_pech_l" "j" "j3"
## [76] "j4" "jigging" "journee"
## [79] "joursin" "lat" "leur_surf"
## [82] "leurre_tt" "ligne_m" "loca_bat"
## [85] "loca_dom" "longueur" "m"
## [88] "m2" "madai" "matin"
## [91] "mod_peche" "mode_eqt" "mort_cru"
## [94] "mort_esp" "mort_mll" "mort_pss"
## [97] "mort_vers" "motor" "moursin"
## [100] "n" "nasse" "nb_ours"
## [103] "nb_pech_o" "nb_pecheur" "nb_sort_an"
## [106] "nb_sort_an6" "nb_sous_tail" "neb"
## [109] "nimp_q" "niql" "nom_asso"
## [112] "nom_esp_ind" "nuit" "o"
## [115] "obs" "obs_stock_l" "obs_stock_o"
## [118] "p_no_kill" "palangre" "palangro"
## [121] "pdb" "pe" "peche_cal"
## [124] "pelote" "phase_lune" "pierre"
## [127] "pierre_bd" "po" "port_atta"
## [130] "poss_bat" "pour_jf" "pourc_sem"
## [133] "pourc_we" "prise_jour" "procu_app"
## [136] "prof_m_moyen" "proximite" "q_esp"
## [139] "quot_max_o" "raison_var" "recommandation"
## [142] "reg_pech_l" "reg_pech_o" "res_alien"
## [145] "res_tour" "rockfish" "s"
## [148] "sais_pech_o" "Saisie" "secteur_po"
## [151] "secteur_po7" "sem" "sexe"
## [154] "shad" "shore_jigg" "soir"
## [157] "solu_gest" "sondeur" "sout_bd"
## [160] "surfcas" "table_traçante" "tail_min_o"
## [163] "temp" "temps_parc" "Temps_peche_effectif"
## [166] "Temps_peche_estime" "tenya" "tra_fond"
## [169] "tra_surf" "tranquilite" "turlutte"
## [172] "type_bat" "vac" "vire_ligne"
## [175] "viv_cru" "viv_esp" "viv_moll"
## [178] "viv_pss" "viv_vers" "vivier"
## [181] "we" "x_degres" "x_lon"
## [184] "x_lon_DD" "x_min_dec" "y_degres"
## [187] "y_lat" "y_lat_DD" "y_min_dec"
## [190] "z_1" "z_2" "z_3"
## [193] "z_4" "z_54" "z_55"
## [196] "z_56" "z_57" "z_58"
## [199] "z_59" "z_6" "z_60"
## [202] "z_61" "z_7" "z_8"
## [205] "z_9" "zone_pro" "y_degre"
## [208] "x_degre" "prof_m" "journée"
## [211] "temps_pêche" "temps_peche_estime"
setdiff(names(survey),Meta.survey$Libellé)
## [1] "a5" "autre10" "autre9"
## [4] "douz_jour8" "j3" "j4"
## [7] "journee" "m2" "nb_sort_an6"
## [10] "Saisie" "secteur_po7" "Temps_peche_effectif"
## [13] "Temps_peche_estime" "x_degres" "y_degres"
survey <- survey[,c(intersect(Meta.survey$Libellé,names(survey)), setdiff(names(survey),Meta.survey$Libellé))]
names. <- names(read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "BDD_enquete_terrain_publique", col_names = T))
survey <- survey[,names.]
rm(names.)
survey <- add_column(survey, BD = "PNMCA", .before = "mode_eqt")
# fishing data
fishing.Stareso <- read_excel("Enquetes_Pêche_Loisir_PNMCCA_Chabrier_2023 (1).xlsx", sheet = "BD_Stareso", col_names = T, col_types = c(
"numeric",
"text",
"text",
"date",
"text",
"numeric",
"numeric",
"text",
"text",
"text",
"text",
"text",
"numeric",
"numeric",
"text",
"text",
"numeric",
"numeric",
"date",
"date",
"date",
"date",
"text",
"text",
"text",
"text", #many geographical zone
"text", #many sites
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"numeric",
"numeric",
"numeric",
"numeric",
"text",
"numeric",
"numeric",
"text"))
## Warning: Expecting numeric in F20 / R20C6: got 'NA'
## Warning: Expecting numeric in G20 / R20C7: got 'NA'
## Warning: Expecting numeric in Q21 / R21C17: got 'NA'
## Warning: Expecting date in S29 / R29C19: got 'NA'
## Warning: Expecting date in U29 / R29C21: got 'NA'
## Warning: Expecting date in V29 / R29C22: got 'NA'
## Warning: Expecting numeric in AK29 / R29C37: got 'NA'
## Warning: Expecting numeric in AL29 / R29C38: got 'NA'
## Warning: Expecting numeric in AM29 / R29C39: got 'NA'
## Warning: Expecting numeric in G40 / R40C7: got 'NA'
## Warning: Expecting numeric in Q40 / R40C17: got 'NA'
## Warning: Expecting numeric in AL40 / R40C38: got 'NA'
## Warning: Expecting numeric in G71 / R71C7: got 'NA'
## Warning: Expecting numeric in G72 / R72C7: got 'NA'
## Warning: Expecting numeric in G103 / R103C7: got 'NA'
## Warning: Expecting numeric in AL186 / R186C38: got 'NA'
## Warning: Expecting numeric in AL187 / R187C38: got 'NA'
## Warning: Expecting numeric in AL188 / R188C38: got 'NA'
## Warning: Expecting numeric in R383 / R383C18: got 'NA'
## Warning: Expecting numeric in AL386 / R386C38: got 'NA'
## Warning: Expecting numeric in AL387 / R387C38: got 'NA'
## Warning: Expecting numeric in AL388 / R388C38: got 'NA'
## Warning: Expecting numeric in AL461 / R461C38: got 'NA'
## Warning: Expecting numeric in AK462 / R462C37: got 'NA'
## Warning: Expecting numeric in AL462 / R462C38: got 'NA'
fishing.Stareso <- filter(fishing.Stareso, !is.na(fiche_n))
head(fishing.Stareso)
## # A tibble: 6 × 44
## fiche_n id_sortie id_obs date saisie etat_mer temp force_vent
## <dbl> <chr> <chr> <dttm> <chr> <dbl> <dbl> <chr>
## 1 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## 2 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## 3 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## 4 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## 5 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## 6 1 <NA> <NA> 2023-06-14 00:00:00 NC 1 21 2
## # ℹ 36 more variables: direct_v <chr>, direct_h <chr>, nebulosite <chr>,
## # phase_lune <chr>, `lat (°N)` <dbl>, `long (°E)` <dbl>, mod_pech <chr>,
## # zone_peche <chr>, prof_m <dbl>, nb_pecheur <dbl>, heure_deb <dttm>,
## # heure_enq <dttm>, heure_fin <dttm>, temps_pech <dttm>,
## # lieu_residence <chr>, mode_de_pêche <chr>, zone_geographique <chr>,
## # choix_site <chr>, fond_rech <chr>, esp_cib <chr>, mort_app <chr>,
## # mort_esp <chr>, viv_app <chr>, viv_esp <chr>, app_autre <chr>, …
names(fishing.Stareso)
## [1] "fiche_n" "id_sortie" "id_obs"
## [4] "date" "saisie" "etat_mer"
## [7] "temp" "force_vent" "direct_v"
## [10] "direct_h" "nebulosite" "phase_lune"
## [13] "lat (°N)" "long (°E)" "mod_pech"
## [16] "zone_peche" "prof_m" "nb_pecheur"
## [19] "heure_deb" "heure_enq" "heure_fin"
## [22] "temps_pech" "lieu_residence" "mode_de_pêche"
## [25] "zone_geographique" "choix_site" "fond_rech"
## [28] "esp_cib" "mort_app" "mort_esp"
## [31] "viv_app" "viv_esp" "app_autre"
## [34] "procu_app" "tech_util" "nom_scien"
## [37] "nb_ind" "tail_cm" "poids_g"
## [40] "poids_sor" "photos" "CPUE"
## [43] "CPUE total" "obs"
fishing.Stareso$heure_deb <- as_hms(fishing.Stareso$heure_deb)
fishing.Stareso$heure_enq <- as_hms(fishing.Stareso$heure_enq)
fishing.Stareso$heure_fin <- as_hms(fishing.Stareso$heure_fin)
fishing.Stareso$temps_pech <- as_hms(fishing.Stareso$temps_pech)
fishing.PNMCA <- read_excel("BDD_peche_loisir_2024_04_18.xlsx", sheet = "BDD_donnees_peche_du_jour", col_names = T, col_types = c(
"numeric",
"text",
"text",
"date",
"text",
"numeric",
"numeric",
"text",
"text",
"text",
"text",
"text",
"numeric",
"numeric",
"numeric",
"numeric",
"text", #lat not in the metadata
"numeric",
"numeric",
"numeric",
"numeric",
"text", #long not in the metadata
"text",
"numeric",
"numeric",
"date",
"date",
"date",
"date",
"date",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text",
"text", #cfr nom_scien not numeric but text, error in the metadata
"numeric",
"numeric",
"numeric",
"numeric", #I add to remove "g" and "-" in pds_sor var 168, 169, 185, 190, 253
"text",
"numeric",
"numeric",
"text"))
## Warning: Expecting numeric in G2 / R2C7: got 'NA'
## Warning: Expecting numeric in M2 / R2C13: got 'NA'
## Warning: Expecting numeric in N2 / R2C14: got 'NA'
## Warning: Expecting numeric in O2 / R2C15: got 'NA'
## Warning: Expecting numeric in R2 / R2C18: got 'NA'
## Warning: Expecting numeric in S2 / R2C19: got 'NA'
## Warning: Expecting numeric in T2 / R2C20: got 'NA'
## Warning: Expecting numeric in G3 / R3C7: got 'NA'
## Warning: Expecting numeric in M3 / R3C13: got 'NA'
## Warning: Expecting numeric in N3 / R3C14: got 'NA'
## Warning: Expecting numeric in O3 / R3C15: got 'NA'
## Warning: Expecting numeric in R3 / R3C18: got 'NA'
## Warning: Expecting numeric in S3 / R3C19: got 'NA'
## Warning: Expecting numeric in T3 / R3C20: got 'NA'
## Warning: Expecting numeric in G4 / R4C7: got 'NA'
## Warning: Expecting numeric in M4 / R4C13: got 'NA'
## Warning: Expecting numeric in N4 / R4C14: got 'NA'
## Warning: Expecting numeric in O4 / R4C15: got 'NA'
## Warning: Expecting numeric in R4 / R4C18: got 'NA'
## Warning: Expecting numeric in S4 / R4C19: got 'NA'
## Warning: Expecting numeric in T4 / R4C20: got 'NA'
## Warning: Expecting numeric in G5 / R5C7: got 'NA'
## Warning: Expecting numeric in M5 / R5C13: got 'NA'
## Warning: Expecting numeric in N5 / R5C14: got 'NA'
## Warning: Expecting numeric in O5 / R5C15: got 'NA'
## Warning: Expecting numeric in R5 / R5C18: got 'NA'
## Warning: Expecting numeric in S5 / R5C19: got 'NA'
## Warning: Expecting numeric in T5 / R5C20: got 'NA'
## Warning: Expecting numeric in G6 / R6C7: got 'NA'
## Warning: Expecting numeric in M6 / R6C13: got 'NA'
## Warning: Expecting numeric in N6 / R6C14: got 'NA'
## Warning: Expecting numeric in O6 / R6C15: got 'NA'
## Warning: Expecting numeric in R6 / R6C18: got 'NA'
## Warning: Expecting numeric in S6 / R6C19: got 'NA'
## Warning: Expecting numeric in T6 / R6C20: got 'NA'
## Warning: Expecting numeric in G7 / R7C7: got 'NA'
## Warning: Expecting numeric in M7 / R7C13: got 'NA'
## Warning: Expecting numeric in N7 / R7C14: got 'NA'
## Warning: Expecting numeric in O7 / R7C15: got 'NA'
## Warning: Expecting numeric in R7 / R7C18: got 'NA'
## Warning: Expecting numeric in S7 / R7C19: got 'NA'
## Warning: Expecting numeric in T7 / R7C20: got 'NA'
## Warning: Expecting numeric in G8 / R8C7: got 'NA'
## Warning: Expecting numeric in M8 / R8C13: got 'NA'
## Warning: Expecting numeric in N8 / R8C14: got 'NA'
## Warning: Expecting numeric in O8 / R8C15: got 'NA'
## Warning: Expecting numeric in R8 / R8C18: got 'NA'
## Warning: Expecting numeric in S8 / R8C19: got 'NA'
## Warning: Expecting numeric in T8 / R8C20: got 'NA'
## Warning: Expecting numeric in G9 / R9C7: got 'NA'
## Warning: Expecting numeric in M9 / R9C13: got 'NA'
## Warning: Expecting numeric in N9 / R9C14: got 'NA'
## Warning: Expecting numeric in O9 / R9C15: got 'NA'
## Warning: Expecting numeric in R9 / R9C18: got 'NA'
## Warning: Expecting numeric in S9 / R9C19: got 'NA'
## Warning: Expecting numeric in T9 / R9C20: got 'NA'
## Warning: Expecting numeric in G10 / R10C7: got 'NA'
## Warning: Expecting numeric in M10 / R10C13: got 'NA'
## Warning: Expecting numeric in N10 / R10C14: got 'NA'
## Warning: Expecting numeric in O10 / R10C15: got 'NA'
## Warning: Expecting numeric in R10 / R10C18: got 'NA'
## Warning: Expecting numeric in S10 / R10C19: got 'NA'
## Warning: Expecting numeric in T10 / R10C20: got 'NA'
## Warning: Expecting numeric in G11 / R11C7: got 'NA'
## Warning: Expecting numeric in M11 / R11C13: got 'NA'
## Warning: Expecting numeric in N11 / R11C14: got 'NA'
## Warning: Expecting numeric in O11 / R11C15: got 'NA'
## Warning: Expecting numeric in R11 / R11C18: got 'NA'
## Warning: Expecting numeric in S11 / R11C19: got 'NA'
## Warning: Expecting numeric in T11 / R11C20: got 'NA'
## Warning: Expecting numeric in G12 / R12C7: got 'NA'
## Warning: Expecting numeric in M12 / R12C13: got 'NA'
## Warning: Expecting numeric in N12 / R12C14: got 'NA'
## Warning: Expecting numeric in O12 / R12C15: got 'NA'
## Warning: Expecting numeric in R12 / R12C18: got 'NA'
## Warning: Expecting numeric in S12 / R12C19: got 'NA'
## Warning: Expecting numeric in T12 / R12C20: got 'NA'
## Warning: Expecting numeric in G13 / R13C7: got 'NA'
## Warning: Expecting numeric in M13 / R13C13: got 'NA'
## Warning: Expecting numeric in N13 / R13C14: got 'NA'
## Warning: Expecting numeric in O13 / R13C15: got 'NA'
## Warning: Expecting numeric in R13 / R13C18: got 'NA'
## Warning: Expecting numeric in S13 / R13C19: got 'NA'
## Warning: Expecting numeric in T13 / R13C20: got 'NA'
## Warning: Expecting numeric in G14 / R14C7: got 'NA'
## Warning: Expecting numeric in M14 / R14C13: got 'NA'
## Warning: Expecting numeric in N14 / R14C14: got 'NA'
## Warning: Expecting numeric in O14 / R14C15: got 'NA'
## Warning: Expecting numeric in R14 / R14C18: got 'NA'
## Warning: Expecting numeric in S14 / R14C19: got 'NA'
## Warning: Expecting numeric in T14 / R14C20: got 'NA'
## Warning: Expecting numeric in G15 / R15C7: got 'NA'
## Warning: Expecting numeric in M15 / R15C13: got 'NA'
## Warning: Expecting numeric in N15 / R15C14: got 'NA'
## Warning: Expecting numeric in O15 / R15C15: got 'NA'
## Warning: Expecting numeric in R15 / R15C18: got 'NA'
## Warning: Expecting numeric in S15 / R15C19: got 'NA'
## Warning: Expecting numeric in T15 / R15C20: got 'NA'
## Warning: Expecting numeric in G16 / R16C7: got 'NA'
## Warning: Expecting numeric in M16 / R16C13: got 'NA'
## Warning: Expecting numeric in N16 / R16C14: got 'NA'
## Warning: Expecting numeric in O16 / R16C15: got 'NA'
## Warning: Expecting numeric in R16 / R16C18: got 'NA'
## Warning: Expecting numeric in S16 / R16C19: got 'NA'
## Warning: Expecting numeric in T16 / R16C20: got 'NA'
## Warning: Expecting numeric in G17 / R17C7: got 'NA'
## Warning: Expecting numeric in M17 / R17C13: got 'NA'
## Warning: Expecting numeric in N17 / R17C14: got 'NA'
## Warning: Expecting numeric in O17 / R17C15: got 'NA'
## Warning: Expecting numeric in R17 / R17C18: got 'NA'
## Warning: Expecting numeric in S17 / R17C19: got 'NA'
## Warning: Expecting numeric in T17 / R17C20: got 'NA'
## Warning: Expecting numeric in G18 / R18C7: got 'NA'
## Warning: Expecting numeric in M18 / R18C13: got 'NA'
## Warning: Expecting numeric in N18 / R18C14: got 'NA'
## Warning: Expecting numeric in O18 / R18C15: got 'NA'
## Warning: Expecting numeric in R18 / R18C18: got 'NA'
## Warning: Expecting numeric in S18 / R18C19: got 'NA'
## Warning: Expecting numeric in T18 / R18C20: got 'NA'
## Warning: Expecting numeric in G19 / R19C7: got 'NA'
## Warning: Expecting numeric in M19 / R19C13: got 'NA'
## Warning: Expecting numeric in N19 / R19C14: got 'NA'
## Warning: Expecting numeric in O19 / R19C15: got 'NA'
## Warning: Expecting numeric in R19 / R19C18: got 'NA'
## Warning: Expecting numeric in S19 / R19C19: got 'NA'
## Warning: Expecting numeric in T19 / R19C20: got 'NA'
## Warning: Expecting numeric in G20 / R20C7: got 'NA'
## Warning: Expecting numeric in M20 / R20C13: got 'NA'
## Warning: Expecting numeric in N20 / R20C14: got 'NA'
## Warning: Expecting numeric in O20 / R20C15: got 'NA'
## Warning: Expecting numeric in R20 / R20C18: got 'NA'
## Warning: Expecting numeric in S20 / R20C19: got 'NA'
## Warning: Expecting numeric in T20 / R20C20: got 'NA'
## Warning: Expecting numeric in G21 / R21C7: got 'NA'
## Warning: Expecting numeric in M21 / R21C13: got 'NA'
## Warning: Expecting numeric in N21 / R21C14: got 'NA'
## Warning: Expecting numeric in O21 / R21C15: got 'NA'
## Warning: Expecting numeric in R21 / R21C18: got 'NA'
## Warning: Expecting numeric in S21 / R21C19: got 'NA'
## Warning: Expecting numeric in T21 / R21C20: got 'NA'
## Warning: Expecting numeric in G22 / R22C7: got 'NA'
## Warning: Expecting numeric in M22 / R22C13: got 'NA'
## Warning: Expecting numeric in N22 / R22C14: got 'NA'
## Warning: Expecting numeric in O22 / R22C15: got 'NA'
## Warning: Expecting numeric in R22 / R22C18: got 'NA'
## Warning: Expecting numeric in S22 / R22C19: got 'NA'
## Warning: Expecting numeric in T22 / R22C20: got 'NA'
## Warning: Expecting numeric in G23 / R23C7: got 'NA'
## Warning: Expecting numeric in M23 / R23C13: got 'NA'
## Warning: Expecting numeric in N23 / R23C14: got 'NA'
## Warning: Expecting numeric in O23 / R23C15: got 'NA'
## Warning: Expecting numeric in R23 / R23C18: got 'NA'
## Warning: Expecting numeric in S23 / R23C19: got 'NA'
## Warning: Expecting numeric in T23 / R23C20: got 'NA'
## Warning: Expecting numeric in G24 / R24C7: got 'NA'
## Warning: Expecting numeric in M24 / R24C13: got 'NA'
## Warning: Expecting numeric in N24 / R24C14: got 'NA'
## Warning: Expecting numeric in O24 / R24C15: got 'NA'
## Warning: Expecting numeric in R24 / R24C18: got 'NA'
## Warning: Expecting numeric in S24 / R24C19: got 'NA'
## Warning: Expecting numeric in T24 / R24C20: got 'NA'
## Warning: Expecting numeric in G25 / R25C7: got 'NA'
## Warning: Expecting numeric in M25 / R25C13: got 'NA'
## Warning: Expecting numeric in N25 / R25C14: got 'NA'
## Warning: Expecting numeric in O25 / R25C15: got 'NA'
## Warning: Expecting numeric in R25 / R25C18: got 'NA'
## Warning: Expecting numeric in S25 / R25C19: got 'NA'
## Warning: Expecting numeric in T25 / R25C20: got 'NA'
## Warning: Expecting numeric in G26 / R26C7: got 'NA'
## Warning: Expecting numeric in M26 / R26C13: got 'NA'
## Warning: Expecting numeric in N26 / R26C14: got 'NA'
## Warning: Expecting numeric in O26 / R26C15: got 'NA'
## Warning: Expecting numeric in R26 / R26C18: got 'NA'
## Warning: Expecting numeric in S26 / R26C19: got 'NA'
## Warning: Expecting numeric in T26 / R26C20: got 'NA'
## Warning: Expecting numeric in G27 / R27C7: got 'NA'
## Warning: Expecting numeric in M27 / R27C13: got 'NA'
## Warning: Expecting numeric in N27 / R27C14: got 'NA'
## Warning: Expecting numeric in O27 / R27C15: got 'NA'
## Warning: Expecting numeric in R27 / R27C18: got 'NA'
## Warning: Expecting numeric in S27 / R27C19: got 'NA'
## Warning: Expecting numeric in T27 / R27C20: got 'NA'
## Warning: Expecting numeric in G28 / R28C7: got 'NA'
## Warning: Expecting numeric in M28 / R28C13: got 'NA'
## Warning: Expecting numeric in N28 / R28C14: got 'NA'
## Warning: Expecting numeric in O28 / R28C15: got 'NA'
## Warning: Expecting numeric in R28 / R28C18: got 'NA'
## Warning: Expecting numeric in S28 / R28C19: got 'NA'
## Warning: Expecting numeric in T28 / R28C20: got 'NA'
## Warning: Expecting numeric in G29 / R29C7: got 'NA'
## Warning: Expecting numeric in M29 / R29C13: got 'NA'
## Warning: Expecting numeric in N29 / R29C14: got 'NA'
## Warning: Expecting numeric in O29 / R29C15: got 'NA'
## Warning: Expecting numeric in R29 / R29C18: got 'NA'
## Warning: Expecting numeric in S29 / R29C19: got 'NA'
## Warning: Expecting numeric in T29 / R29C20: got 'NA'
## Warning: Expecting numeric in G30 / R30C7: got 'NA'
## Warning: Expecting numeric in M30 / R30C13: got 'NA'
## Warning: Expecting numeric in N30 / R30C14: got 'NA'
## Warning: Expecting numeric in O30 / R30C15: got 'NA'
## Warning: Expecting numeric in R30 / R30C18: got 'NA'
## Warning: Expecting numeric in S30 / R30C19: got 'NA'
## Warning: Expecting numeric in T30 / R30C20: got 'NA'
## Warning: Expecting numeric in G31 / R31C7: got 'NA'
## Warning: Expecting numeric in M31 / R31C13: got 'NA'
## Warning: Expecting numeric in N31 / R31C14: got 'NA'
## Warning: Expecting numeric in O31 / R31C15: got 'NA'
## Warning: Expecting numeric in R31 / R31C18: got 'NA'
## Warning: Expecting numeric in S31 / R31C19: got 'NA'
## Warning: Expecting numeric in T31 / R31C20: got 'NA'
## Warning: Expecting numeric in G32 / R32C7: got 'NA'
## Warning: Expecting numeric in M32 / R32C13: got 'NA'
## Warning: Expecting numeric in N32 / R32C14: got 'NA'
## Warning: Expecting numeric in O32 / R32C15: got 'NA'
## Warning: Expecting numeric in R32 / R32C18: got 'NA'
## Warning: Expecting numeric in S32 / R32C19: got 'NA'
## Warning: Expecting numeric in T32 / R32C20: got 'NA'
## Warning: Expecting numeric in G33 / R33C7: got 'NA'
## Warning: Expecting numeric in M33 / R33C13: got 'NA'
## Warning: Expecting numeric in N33 / R33C14: got 'NA'
## Warning: Expecting numeric in O33 / R33C15: got 'NA'
## Warning: Expecting numeric in R33 / R33C18: got 'NA'
## Warning: Expecting numeric in S33 / R33C19: got 'NA'
## Warning: Expecting numeric in T33 / R33C20: got 'NA'
## Warning: Expecting numeric in G34 / R34C7: got 'NA'
## Warning: Expecting numeric in M34 / R34C13: got 'NA'
## Warning: Expecting numeric in N34 / R34C14: got 'NA'
## Warning: Expecting numeric in O34 / R34C15: got 'NA'
## Warning: Expecting numeric in R34 / R34C18: got 'NA'
## Warning: Expecting numeric in S34 / R34C19: got 'NA'
## Warning: Expecting numeric in T34 / R34C20: got 'NA'
## Warning: Expecting numeric in G35 / R35C7: got 'NA'
## Warning: Expecting numeric in M35 / R35C13: got 'NA'
## Warning: Expecting numeric in N35 / R35C14: got 'NA'
## Warning: Expecting numeric in O35 / R35C15: got 'NA'
## Warning: Expecting numeric in R35 / R35C18: got 'NA'
## Warning: Expecting numeric in S35 / R35C19: got 'NA'
## Warning: Expecting numeric in T35 / R35C20: got 'NA'
## Warning: Expecting numeric in G36 / R36C7: got 'NA'
## Warning: Expecting numeric in M36 / R36C13: got 'NA'
## Warning: Expecting numeric in N36 / R36C14: got 'NA'
## Warning: Expecting numeric in O36 / R36C15: got 'NA'
## Warning: Expecting numeric in R36 / R36C18: got 'NA'
## Warning: Expecting numeric in S36 / R36C19: got 'NA'
## Warning: Expecting numeric in T36 / R36C20: got 'NA'
## Warning: Expecting numeric in G37 / R37C7: got 'NA'
## Warning: Expecting numeric in M37 / R37C13: got 'NA'
## Warning: Expecting numeric in N37 / R37C14: got 'NA'
## Warning: Expecting numeric in O37 / R37C15: got 'NA'
## Warning: Expecting numeric in R37 / R37C18: got 'NA'
## Warning: Expecting numeric in S37 / R37C19: got 'NA'
## Warning: Expecting numeric in T37 / R37C20: got 'NA'
## Warning: Expecting numeric in G38 / R38C7: got 'NA'
## Warning: Expecting numeric in M38 / R38C13: got 'NA'
## Warning: Expecting numeric in N38 / R38C14: got 'NA'
## Warning: Expecting numeric in O38 / R38C15: got 'NA'
## Warning: Expecting numeric in R38 / R38C18: got 'NA'
## Warning: Expecting numeric in S38 / R38C19: got 'NA'
## Warning: Expecting numeric in T38 / R38C20: got 'NA'
## Warning: Expecting numeric in G39 / R39C7: got 'NA'
## Warning: Expecting numeric in M39 / R39C13: got 'NA'
## Warning: Expecting numeric in N39 / R39C14: got 'NA'
## Warning: Expecting numeric in O39 / R39C15: got 'NA'
## Warning: Expecting numeric in R39 / R39C18: got 'NA'
## Warning: Expecting numeric in S39 / R39C19: got 'NA'
## Warning: Expecting numeric in T39 / R39C20: got 'NA'
## Warning: Expecting numeric in G40 / R40C7: got 'NA'
## Warning: Expecting numeric in M40 / R40C13: got 'NA'
## Warning: Expecting numeric in N40 / R40C14: got 'NA'
## Warning: Expecting numeric in O40 / R40C15: got 'NA'
## Warning: Expecting numeric in R40 / R40C18: got 'NA'
## Warning: Expecting numeric in S40 / R40C19: got 'NA'
## Warning: Expecting numeric in T40 / R40C20: got 'NA'
## Warning: Expecting numeric in G41 / R41C7: got 'NA'
## Warning: Expecting numeric in M41 / R41C13: got 'NA'
## Warning: Expecting numeric in N41 / R41C14: got 'NA'
## Warning: Expecting numeric in O41 / R41C15: got 'NA'
## Warning: Expecting numeric in R41 / R41C18: got 'NA'
## Warning: Expecting numeric in S41 / R41C19: got 'NA'
## Warning: Expecting numeric in T41 / R41C20: got 'NA'
## Warning: Expecting numeric in G42 / R42C7: got 'NA'
## Warning: Expecting numeric in M42 / R42C13: got 'NA'
## Warning: Expecting numeric in N42 / R42C14: got 'NA'
## Warning: Expecting numeric in O42 / R42C15: got 'NA'
## Warning: Expecting numeric in R42 / R42C18: got 'NA'
## Warning: Expecting numeric in S42 / R42C19: got 'NA'
## Warning: Expecting numeric in T42 / R42C20: got 'NA'
## Warning: Expecting numeric in G43 / R43C7: got 'NA'
## Warning: Expecting numeric in M43 / R43C13: got 'NA'
## Warning: Expecting numeric in N43 / R43C14: got 'NA'
## Warning: Expecting numeric in O43 / R43C15: got 'NA'
## Warning: Expecting numeric in R43 / R43C18: got 'NA'
## Warning: Expecting numeric in S43 / R43C19: got 'NA'
## Warning: Expecting numeric in T43 / R43C20: got 'NA'
## Warning: Expecting numeric in G44 / R44C7: got 'NA'
## Warning: Expecting numeric in M44 / R44C13: got 'NA'
## Warning: Expecting numeric in N44 / R44C14: got 'NA'
## Warning: Expecting numeric in O44 / R44C15: got 'NA'
## Warning: Expecting numeric in R44 / R44C18: got 'NA'
## Warning: Expecting numeric in S44 / R44C19: got 'NA'
## Warning: Expecting numeric in T44 / R44C20: got 'NA'
## Warning: Expecting numeric in G45 / R45C7: got 'NA'
## Warning: Expecting numeric in M45 / R45C13: got 'NA'
## Warning: Expecting numeric in N45 / R45C14: got 'NA'
## Warning: Expecting numeric in O45 / R45C15: got 'NA'
## Warning: Expecting numeric in R45 / R45C18: got 'NA'
## Warning: Expecting numeric in S45 / R45C19: got 'NA'
## Warning: Expecting numeric in T45 / R45C20: got 'NA'
## Warning: Expecting numeric in G46 / R46C7: got 'NA'
## Warning: Expecting numeric in M46 / R46C13: got 'NA'
## Warning: Expecting numeric in N46 / R46C14: got 'NA'
## Warning: Expecting numeric in O46 / R46C15: got 'NA'
## Warning: Expecting numeric in R46 / R46C18: got 'NA'
## Warning: Expecting numeric in S46 / R46C19: got 'NA'
## Warning: Expecting numeric in T46 / R46C20: got 'NA'
## Warning: Expecting numeric in G47 / R47C7: got 'NA'
## Warning: Expecting numeric in M47 / R47C13: got 'NA'
## Warning: Expecting numeric in N47 / R47C14: got 'NA'
## Warning: Expecting numeric in O47 / R47C15: got 'NA'
## Warning: Expecting numeric in R47 / R47C18: got 'NA'
## Warning: Expecting numeric in S47 / R47C19: got 'NA'
## Warning: Expecting numeric in T47 / R47C20: got 'NA'
## Warning: Expecting numeric in G48 / R48C7: got 'NA'
## Warning: Expecting numeric in M48 / R48C13: got 'NA'
## Warning: Expecting numeric in N48 / R48C14: got 'NA'
## Warning: Expecting numeric in O48 / R48C15: got 'NA'
## Warning: Expecting numeric in R48 / R48C18: got 'NA'
## Warning: Expecting numeric in S48 / R48C19: got 'NA'
## Warning: Expecting numeric in T48 / R48C20: got 'NA'
## Warning: Expecting numeric in G49 / R49C7: got 'NA'
## Warning: Expecting numeric in M49 / R49C13: got 'NA'
## Warning: Expecting numeric in N49 / R49C14: got 'NA'
## Warning: Expecting numeric in O49 / R49C15: got 'NA'
## Warning: Expecting numeric in R49 / R49C18: got 'NA'
## Warning: Expecting numeric in S49 / R49C19: got 'NA'
## Warning: Expecting numeric in T49 / R49C20: got 'NA'
## Warning: Expecting numeric in G50 / R50C7: got 'NA'
## Warning: Expecting numeric in M50 / R50C13: got 'NA'
## Warning: Expecting numeric in N50 / R50C14: got 'NA'
## Warning: Expecting numeric in O50 / R50C15: got 'NA'
## Warning: Expecting numeric in R50 / R50C18: got 'NA'
## Warning: Expecting numeric in S50 / R50C19: got 'NA'
## Warning: Expecting numeric in T50 / R50C20: got 'NA'
## Warning: Expecting numeric in G51 / R51C7: got 'NA'
## Warning: Expecting numeric in M51 / R51C13: got 'NA'
## Warning: Expecting numeric in N51 / R51C14: got 'NA'
## Warning: Expecting numeric in O51 / R51C15: got 'NA'
## Warning: Expecting numeric in R51 / R51C18: got 'NA'
## Warning: Expecting numeric in S51 / R51C19: got 'NA'
## Warning: Expecting numeric in T51 / R51C20: got 'NA'
## Warning: Expecting numeric in G52 / R52C7: got 'NA'
## Warning: Expecting numeric in M52 / R52C13: got 'NA'
## Warning: Expecting numeric in N52 / R52C14: got 'NA'
## Warning: Expecting numeric in O52 / R52C15: got 'NA'
## Warning: Expecting numeric in R52 / R52C18: got 'NA'
## Warning: Expecting numeric in S52 / R52C19: got 'NA'
## Warning: Expecting numeric in T52 / R52C20: got 'NA'
## Warning: Expecting numeric in G53 / R53C7: got 'NA'
## Warning: Expecting numeric in M53 / R53C13: got 'NA'
## Warning: Expecting numeric in N53 / R53C14: got 'NA'
## Warning: Expecting numeric in O53 / R53C15: got 'NA'
## Warning: Expecting numeric in R53 / R53C18: got 'NA'
## Warning: Expecting numeric in S53 / R53C19: got 'NA'
## Warning: Expecting numeric in T53 / R53C20: got 'NA'
## Warning: Expecting numeric in AT53 / R53C46: got 'NA'
## Warning: Expecting numeric in G54 / R54C7: got 'NA'
## Warning: Expecting numeric in M54 / R54C13: got 'NA'
## Warning: Expecting numeric in N54 / R54C14: got 'NA'
## Warning: Expecting numeric in O54 / R54C15: got 'NA'
## Warning: Expecting numeric in R54 / R54C18: got 'NA'
## Warning: Expecting numeric in S54 / R54C19: got 'NA'
## Warning: Expecting numeric in T54 / R54C20: got 'NA'
## Warning: Expecting numeric in G55 / R55C7: got 'NA'
## Warning: Expecting numeric in M55 / R55C13: got 'NA'
## Warning: Expecting numeric in N55 / R55C14: got 'NA'
## Warning: Expecting numeric in O55 / R55C15: got 'NA'
## Warning: Expecting numeric in R55 / R55C18: got 'NA'
## Warning: Expecting numeric in S55 / R55C19: got 'NA'
## Warning: Expecting numeric in T55 / R55C20: got 'NA'
## Warning: Expecting numeric in G56 / R56C7: got 'NA'
## Warning: Expecting numeric in M56 / R56C13: got 'NA'
## Warning: Expecting numeric in N56 / R56C14: got 'NA'
## Warning: Expecting numeric in O56 / R56C15: got 'NA'
## Warning: Expecting numeric in R56 / R56C18: got 'NA'
## Warning: Expecting numeric in S56 / R56C19: got 'NA'
## Warning: Expecting numeric in T56 / R56C20: got 'NA'
## Warning: Expecting numeric in G57 / R57C7: got 'NA'
## Warning: Expecting numeric in M57 / R57C13: got 'NA'
## Warning: Expecting numeric in N57 / R57C14: got 'NA'
## Warning: Expecting numeric in O57 / R57C15: got 'NA'
## Warning: Expecting numeric in R57 / R57C18: got 'NA'
## Warning: Expecting numeric in S57 / R57C19: got 'NA'
## Warning: Expecting numeric in T57 / R57C20: got 'NA'
## Warning: Expecting numeric in G58 / R58C7: got 'NA'
## Warning: Expecting numeric in M58 / R58C13: got 'NA'
## Warning: Expecting numeric in N58 / R58C14: got 'NA'
## Warning: Expecting numeric in O58 / R58C15: got 'NA'
## Warning: Expecting numeric in R58 / R58C18: got 'NA'
## Warning: Expecting numeric in S58 / R58C19: got 'NA'
## Warning: Expecting numeric in T58 / R58C20: got 'NA'
## Warning: Expecting numeric in G59 / R59C7: got 'NA'
## Warning: Expecting numeric in M59 / R59C13: got 'NA'
## Warning: Expecting numeric in N59 / R59C14: got 'NA'
## Warning: Expecting numeric in O59 / R59C15: got 'NA'
## Warning: Expecting numeric in R59 / R59C18: got 'NA'
## Warning: Expecting numeric in S59 / R59C19: got 'NA'
## Warning: Expecting numeric in T59 / R59C20: got 'NA'
## Warning: Expecting numeric in G60 / R60C7: got 'NA'
## Warning: Expecting numeric in M60 / R60C13: got 'NA'
## Warning: Expecting numeric in N60 / R60C14: got 'NA'
## Warning: Expecting numeric in O60 / R60C15: got 'NA'
## Warning: Expecting numeric in R60 / R60C18: got 'NA'
## Warning: Expecting numeric in S60 / R60C19: got 'NA'
## Warning: Expecting numeric in T60 / R60C20: got 'NA'
## Warning: Expecting numeric in G61 / R61C7: got 'NA'
## Warning: Expecting numeric in M61 / R61C13: got 'NA'
## Warning: Expecting numeric in N61 / R61C14: got 'NA'
## Warning: Expecting numeric in O61 / R61C15: got 'NA'
## Warning: Expecting numeric in R61 / R61C18: got 'NA'
## Warning: Expecting numeric in S61 / R61C19: got 'NA'
## Warning: Expecting numeric in T61 / R61C20: got 'NA'
## Warning: Expecting numeric in G62 / R62C7: got 'NA'
## Warning: Expecting numeric in M62 / R62C13: got 'NA'
## Warning: Expecting numeric in N62 / R62C14: got 'NA'
## Warning: Expecting numeric in O62 / R62C15: got 'NA'
## Warning: Expecting numeric in R62 / R62C18: got 'NA'
## Warning: Expecting numeric in S62 / R62C19: got 'NA'
## Warning: Expecting numeric in T62 / R62C20: got 'NA'
## Warning: Expecting numeric in G63 / R63C7: got 'NA'
## Warning: Expecting numeric in M63 / R63C13: got 'NA'
## Warning: Expecting numeric in N63 / R63C14: got 'NA'
## Warning: Expecting numeric in O63 / R63C15: got 'NA'
## Warning: Expecting numeric in R63 / R63C18: got 'NA'
## Warning: Expecting numeric in S63 / R63C19: got 'NA'
## Warning: Expecting numeric in T63 / R63C20: got 'NA'
## Warning: Expecting numeric in AU63 / R63C47: got 'NA'
## Warning: Expecting numeric in AV63 / R63C48: got 'NA'
## Warning: Expecting numeric in G64 / R64C7: got 'NA'
## Warning: Expecting numeric in M64 / R64C13: got 'NA'
## Warning: Expecting numeric in N64 / R64C14: got 'NA'
## Warning: Expecting numeric in O64 / R64C15: got 'NA'
## Warning: Expecting numeric in R64 / R64C18: got 'NA'
## Warning: Expecting numeric in S64 / R64C19: got 'NA'
## Warning: Expecting numeric in T64 / R64C20: got 'NA'
## Warning: Expecting numeric in G65 / R65C7: got 'NA'
## Warning: Expecting numeric in M65 / R65C13: got 'NA'
## Warning: Expecting numeric in N65 / R65C14: got 'NA'
## Warning: Expecting numeric in O65 / R65C15: got 'NA'
## Warning: Expecting numeric in R65 / R65C18: got 'NA'
## Warning: Expecting numeric in S65 / R65C19: got 'NA'
## Warning: Expecting numeric in T65 / R65C20: got 'NA'
## Warning: Expecting numeric in G66 / R66C7: got 'NA'
## Warning: Expecting numeric in M66 / R66C13: got 'NA'
## Warning: Expecting numeric in N66 / R66C14: got 'NA'
## Warning: Expecting numeric in O66 / R66C15: got 'NA'
## Warning: Expecting numeric in R66 / R66C18: got 'NA'
## Warning: Expecting numeric in S66 / R66C19: got 'NA'
## Warning: Expecting numeric in T66 / R66C20: got 'NA'
## Warning: Expecting numeric in G67 / R67C7: got 'NA'
## Warning: Expecting numeric in M67 / R67C13: got 'NA'
## Warning: Expecting numeric in N67 / R67C14: got 'NA'
## Warning: Expecting numeric in O67 / R67C15: got 'NA'
## Warning: Expecting numeric in R67 / R67C18: got 'NA'
## Warning: Expecting numeric in S67 / R67C19: got 'NA'
## Warning: Expecting numeric in T67 / R67C20: got 'NA'
## Warning: Expecting numeric in G68 / R68C7: got 'NA'
## Warning: Expecting numeric in M68 / R68C13: got 'NA'
## Warning: Expecting numeric in N68 / R68C14: got 'NA'
## Warning: Expecting numeric in O68 / R68C15: got 'NA'
## Warning: Expecting numeric in R68 / R68C18: got 'NA'
## Warning: Expecting numeric in S68 / R68C19: got 'NA'
## Warning: Expecting numeric in T68 / R68C20: got 'NA'
## Warning: Expecting numeric in G69 / R69C7: got 'NA'
## Warning: Expecting numeric in M69 / R69C13: got 'NA'
## Warning: Expecting numeric in N69 / R69C14: got 'NA'
## Warning: Expecting numeric in O69 / R69C15: got 'NA'
## Warning: Expecting numeric in R69 / R69C18: got 'NA'
## Warning: Expecting numeric in S69 / R69C19: got 'NA'
## Warning: Expecting numeric in T69 / R69C20: got 'NA'
## Warning: Expecting numeric in G70 / R70C7: got 'NA'
## Warning: Expecting numeric in M70 / R70C13: got 'NA'
## Warning: Expecting numeric in N70 / R70C14: got 'NA'
## Warning: Expecting numeric in O70 / R70C15: got 'NA'
## Warning: Expecting numeric in R70 / R70C18: got 'NA'
## Warning: Expecting numeric in S70 / R70C19: got 'NA'
## Warning: Expecting numeric in T70 / R70C20: got 'NA'
## Warning: Expecting numeric in G71 / R71C7: got 'NA'
## Warning: Expecting numeric in M71 / R71C13: got 'NA'
## Warning: Expecting numeric in N71 / R71C14: got 'NA'
## Warning: Expecting numeric in O71 / R71C15: got 'NA'
## Warning: Expecting numeric in R71 / R71C18: got 'NA'
## Warning: Expecting numeric in S71 / R71C19: got 'NA'
## Warning: Expecting numeric in T71 / R71C20: got 'NA'
## Warning: Expecting numeric in G72 / R72C7: got 'NA'
## Warning: Expecting numeric in M72 / R72C13: got 'NA'
## Warning: Expecting numeric in N72 / R72C14: got 'NA'
## Warning: Expecting numeric in O72 / R72C15: got 'NA'
## Warning: Expecting numeric in R72 / R72C18: got 'NA'
## Warning: Expecting numeric in S72 / R72C19: got 'NA'
## Warning: Expecting numeric in T72 / R72C20: got 'NA'
## Warning: Expecting numeric in G73 / R73C7: got 'NA'
## Warning: Expecting numeric in M73 / R73C13: got 'NA'
## Warning: Expecting numeric in N73 / R73C14: got 'NA'
## Warning: Expecting numeric in O73 / R73C15: got 'NA'
## Warning: Expecting numeric in R73 / R73C18: got 'NA'
## Warning: Expecting numeric in S73 / R73C19: got 'NA'
## Warning: Expecting numeric in T73 / R73C20: got 'NA'
## Warning: Expecting numeric in G74 / R74C7: got 'NA'
## Warning: Expecting numeric in M74 / R74C13: got 'NA'
## Warning: Expecting numeric in N74 / R74C14: got 'NA'
## Warning: Expecting numeric in O74 / R74C15: got 'NA'
## Warning: Expecting numeric in R74 / R74C18: got 'NA'
## Warning: Expecting numeric in S74 / R74C19: got 'NA'
## Warning: Expecting numeric in T74 / R74C20: got 'NA'
## Warning: Expecting numeric in G75 / R75C7: got 'NA'
## Warning: Expecting numeric in M75 / R75C13: got 'NA'
## Warning: Expecting numeric in N75 / R75C14: got 'NA'
## Warning: Expecting numeric in O75 / R75C15: got 'NA'
## Warning: Expecting numeric in R75 / R75C18: got 'NA'
## Warning: Expecting numeric in S75 / R75C19: got 'NA'
## Warning: Expecting numeric in T75 / R75C20: got 'NA'
## Warning: Expecting numeric in G76 / R76C7: got 'NA'
## Warning: Expecting numeric in M76 / R76C13: got 'NA'
## Warning: Expecting numeric in N76 / R76C14: got 'NA'
## Warning: Expecting numeric in O76 / R76C15: got 'NA'
## Warning: Expecting numeric in R76 / R76C18: got 'NA'
## Warning: Expecting numeric in S76 / R76C19: got 'NA'
## Warning: Expecting numeric in T76 / R76C20: got 'NA'
## Warning: Expecting numeric in G77 / R77C7: got 'NA'
## Warning: Expecting numeric in M77 / R77C13: got 'NA'
## Warning: Expecting numeric in N77 / R77C14: got 'NA'
## Warning: Expecting numeric in O77 / R77C15: got 'NA'
## Warning: Expecting numeric in R77 / R77C18: got 'NA'
## Warning: Expecting numeric in S77 / R77C19: got 'NA'
## Warning: Expecting numeric in T77 / R77C20: got 'NA'
## Warning: Expecting numeric in X77 / R77C24: got 'NA'
## Warning: Expecting numeric in G78 / R78C7: got 'NA'
## Warning: Expecting numeric in M78 / R78C13: got 'NA'
## Warning: Expecting numeric in N78 / R78C14: got 'NA'
## Warning: Expecting numeric in O78 / R78C15: got 'NA'
## Warning: Expecting numeric in R78 / R78C18: got 'NA'
## Warning: Expecting numeric in S78 / R78C19: got 'NA'
## Warning: Expecting numeric in T78 / R78C20: got 'NA'
## Warning: Expecting numeric in G79 / R79C7: got 'NA'
## Warning: Expecting numeric in M79 / R79C13: got 'NA'
## Warning: Expecting numeric in N79 / R79C14: got 'NA'
## Warning: Expecting numeric in O79 / R79C15: got 'NA'
## Warning: Expecting numeric in R79 / R79C18: got 'NA'
## Warning: Expecting numeric in S79 / R79C19: got 'NA'
## Warning: Expecting numeric in T79 / R79C20: got 'NA'
## Warning: Expecting numeric in G80 / R80C7: got 'NA'
## Warning: Expecting numeric in M80 / R80C13: got 'NA'
## Warning: Expecting numeric in N80 / R80C14: got 'NA'
## Warning: Expecting numeric in O80 / R80C15: got 'NA'
## Warning: Expecting numeric in R80 / R80C18: got 'NA'
## Warning: Expecting numeric in S80 / R80C19: got 'NA'
## Warning: Expecting numeric in T80 / R80C20: got 'NA'
## Warning: Expecting numeric in G81 / R81C7: got 'NA'
## Warning: Expecting numeric in M81 / R81C13: got 'NA'
## Warning: Expecting numeric in N81 / R81C14: got 'NA'
## Warning: Expecting numeric in O81 / R81C15: got 'NA'
## Warning: Expecting numeric in R81 / R81C18: got 'NA'
## Warning: Expecting numeric in S81 / R81C19: got 'NA'
## Warning: Expecting numeric in T81 / R81C20: got 'NA'
## Warning: Expecting numeric in G82 / R82C7: got 'NA'
## Warning: Expecting numeric in M82 / R82C13: got 'NA'
## Warning: Expecting numeric in N82 / R82C14: got 'NA'
## Warning: Expecting numeric in O82 / R82C15: got 'NA'
## Warning: Expecting numeric in R82 / R82C18: got 'NA'
## Warning: Expecting numeric in S82 / R82C19: got 'NA'
## Warning: Expecting numeric in T82 / R82C20: got 'NA'
## Warning: Expecting numeric in X82 / R82C24: got 'NA'
## Warning: Expecting numeric in G83 / R83C7: got 'NA'
## Warning: Expecting numeric in M83 / R83C13: got 'NA'
## Warning: Expecting numeric in N83 / R83C14: got 'NA'
## Warning: Expecting numeric in O83 / R83C15: got 'NA'
## Warning: Expecting numeric in R83 / R83C18: got 'NA'
## Warning: Expecting numeric in S83 / R83C19: got 'NA'
## Warning: Expecting numeric in T83 / R83C20: got 'NA'
## Warning: Expecting numeric in X83 / R83C24: got 'NA'
## Warning: Expecting numeric in AY83 / R83C51: got 'NA'
## Warning: Expecting numeric in G84 / R84C7: got 'NA'
## Warning: Expecting numeric in M84 / R84C13: got 'NA'
## Warning: Expecting numeric in N84 / R84C14: got 'NA'
## Warning: Expecting numeric in O84 / R84C15: got 'NA'
## Warning: Expecting numeric in R84 / R84C18: got 'NA'
## Warning: Expecting numeric in S84 / R84C19: got 'NA'
## Warning: Expecting numeric in T84 / R84C20: got 'NA'
## Warning: Expecting numeric in X84 / R84C24: got 'NA'
## Warning: Expecting numeric in AY84 / R84C51: got 'NA'
## Warning: Expecting numeric in G85 / R85C7: got 'NA'
## Warning: Expecting numeric in M85 / R85C13: got 'NA'
## Warning: Expecting numeric in N85 / R85C14: got 'NA'
## Warning: Expecting numeric in O85 / R85C15: got 'NA'
## Warning: Expecting numeric in R85 / R85C18: got 'NA'
## Warning: Expecting numeric in S85 / R85C19: got 'NA'
## Warning: Expecting numeric in T85 / R85C20: got 'NA'
## Warning: Expecting numeric in AY85 / R85C51: got 'NA'
## Warning: Expecting numeric in G86 / R86C7: got 'NA'
## Warning: Expecting numeric in M86 / R86C13: got 'NA'
## Warning: Expecting numeric in N86 / R86C14: got 'NA'
## Warning: Expecting numeric in O86 / R86C15: got 'NA'
## Warning: Expecting numeric in R86 / R86C18: got 'NA'
## Warning: Expecting numeric in S86 / R86C19: got 'NA'
## Warning: Expecting numeric in T86 / R86C20: got 'NA'
## Warning: Expecting numeric in X86 / R86C24: got 'NA'
## Warning: Expecting numeric in AY86 / R86C51: got 'NA'
## Warning: Expecting numeric in G87 / R87C7: got 'NA'
## Warning: Expecting numeric in M87 / R87C13: got 'NA'
## Warning: Expecting numeric in N87 / R87C14: got 'NA'
## Warning: Expecting numeric in O87 / R87C15: got 'NA'
## Warning: Expecting numeric in R87 / R87C18: got 'NA'
## Warning: Expecting numeric in S87 / R87C19: got 'NA'
## Warning: Expecting numeric in T87 / R87C20: got 'NA'
## Warning: Expecting numeric in AY87 / R87C51: got 'NA'
## Warning: Expecting numeric in G88 / R88C7: got 'NA'
## Warning: Expecting numeric in M88 / R88C13: got 'NA'
## Warning: Expecting numeric in N88 / R88C14: got 'NA'
## Warning: Expecting numeric in O88 / R88C15: got 'NA'
## Warning: Expecting numeric in R88 / R88C18: got 'NA'
## Warning: Expecting numeric in S88 / R88C19: got 'NA'
## Warning: Expecting numeric in T88 / R88C20: got 'NA'
## Warning: Expecting numeric in AY88 / R88C51: got 'NA'
## Warning: Expecting numeric in G89 / R89C7: got 'NA'
## Warning: Expecting numeric in M89 / R89C13: got 'NA'
## Warning: Expecting numeric in N89 / R89C14: got 'NA'
## Warning: Expecting numeric in O89 / R89C15: got 'NA'
## Warning: Expecting numeric in R89 / R89C18: got 'NA'
## Warning: Expecting numeric in S89 / R89C19: got 'NA'
## Warning: Expecting numeric in T89 / R89C20: got 'NA'
## Warning: Expecting numeric in AY89 / R89C51: got 'NA'
## Warning: Expecting numeric in G90 / R90C7: got 'NA'
## Warning: Expecting numeric in M90 / R90C13: got 'NA'
## Warning: Expecting numeric in N90 / R90C14: got 'NA'
## Warning: Expecting numeric in O90 / R90C15: got 'NA'
## Warning: Expecting numeric in R90 / R90C18: got 'NA'
## Warning: Expecting numeric in S90 / R90C19: got 'NA'
## Warning: Expecting numeric in T90 / R90C20: got 'NA'
## Warning: Expecting numeric in AY90 / R90C51: got 'NA'
## Warning: Expecting numeric in G91 / R91C7: got 'NA'
## Warning: Expecting numeric in M91 / R91C13: got 'NA'
## Warning: Expecting numeric in N91 / R91C14: got 'NA'
## Warning: Expecting numeric in O91 / R91C15: got 'NA'
## Warning: Expecting numeric in R91 / R91C18: got 'NA'
## Warning: Expecting numeric in S91 / R91C19: got 'NA'
## Warning: Expecting numeric in T91 / R91C20: got 'NA'
## Warning: Expecting numeric in AY91 / R91C51: got 'NA'
## Warning: Expecting numeric in G92 / R92C7: got 'NA'
## Warning: Expecting numeric in M92 / R92C13: got 'NA'
## Warning: Expecting numeric in N92 / R92C14: got 'NA'
## Warning: Expecting numeric in O92 / R92C15: got 'NA'
## Warning: Expecting numeric in R92 / R92C18: got 'NA'
## Warning: Expecting numeric in S92 / R92C19: got 'NA'
## Warning: Expecting numeric in T92 / R92C20: got 'NA'
## Warning: Expecting numeric in AY92 / R92C51: got 'NA'
## Warning: Expecting numeric in G93 / R93C7: got 'NA'
## Warning: Expecting numeric in M93 / R93C13: got 'NA'
## Warning: Expecting numeric in N93 / R93C14: got 'NA'
## Warning: Expecting numeric in O93 / R93C15: got 'NA'
## Warning: Expecting numeric in R93 / R93C18: got 'NA'
## Warning: Expecting numeric in S93 / R93C19: got 'NA'
## Warning: Expecting numeric in T93 / R93C20: got 'NA'
## Warning: Expecting numeric in AY93 / R93C51: got 'NA'
## Warning: Expecting numeric in G94 / R94C7: got 'NA'
## Warning: Expecting numeric in M94 / R94C13: got 'NA'
## Warning: Expecting numeric in N94 / R94C14: got 'NA'
## Warning: Expecting numeric in O94 / R94C15: got 'NA'
## Warning: Expecting numeric in R94 / R94C18: got 'NA'
## Warning: Expecting numeric in S94 / R94C19: got 'NA'
## Warning: Expecting numeric in T94 / R94C20: got 'NA'
## Warning: Expecting numeric in AY94 / R94C51: got 'NA'
## Warning: Expecting numeric in G95 / R95C7: got 'NA'
## Warning: Expecting numeric in M95 / R95C13: got 'NA'
## Warning: Expecting numeric in N95 / R95C14: got 'NA'
## Warning: Expecting numeric in O95 / R95C15: got 'NA'
## Warning: Expecting numeric in R95 / R95C18: got 'NA'
## Warning: Expecting numeric in S95 / R95C19: got 'NA'
## Warning: Expecting numeric in T95 / R95C20: got 'NA'
## Warning: Expecting numeric in AY95 / R95C51: got 'NA'
## Warning: Expecting numeric in G96 / R96C7: got 'NA'
## Warning: Expecting numeric in M96 / R96C13: got 'NA'
## Warning: Expecting numeric in N96 / R96C14: got 'NA'
## Warning: Expecting numeric in O96 / R96C15: got 'NA'
## Warning: Expecting numeric in R96 / R96C18: got 'NA'
## Warning: Expecting numeric in S96 / R96C19: got 'NA'
## Warning: Expecting numeric in T96 / R96C20: got 'NA'
## Warning: Expecting numeric in AY96 / R96C51: got 'NA'
## Warning: Expecting numeric in G97 / R97C7: got 'NA'
## Warning: Expecting numeric in M97 / R97C13: got 'NA'
## Warning: Expecting numeric in N97 / R97C14: got 'NA'
## Warning: Expecting numeric in O97 / R97C15: got 'NA'
## Warning: Expecting numeric in R97 / R97C18: got 'NA'
## Warning: Expecting numeric in S97 / R97C19: got 'NA'
## Warning: Expecting numeric in T97 / R97C20: got 'NA'
## Warning: Expecting numeric in AY97 / R97C51: got 'NA'
## Warning: Expecting numeric in G98 / R98C7: got 'NA'
## Warning: Expecting numeric in M98 / R98C13: got 'NA'
## Warning: Expecting numeric in N98 / R98C14: got 'NA'
## Warning: Expecting numeric in O98 / R98C15: got 'NA'
## Warning: Expecting numeric in R98 / R98C18: got 'NA'
## Warning: Expecting numeric in S98 / R98C19: got 'NA'
## Warning: Expecting numeric in T98 / R98C20: got 'NA'
## Warning: Expecting numeric in AY98 / R98C51: got 'NA'
## Warning: Expecting numeric in G99 / R99C7: got 'NA'
## Warning: Expecting numeric in M99 / R99C13: got 'NA'
## Warning: Expecting numeric in N99 / R99C14: got 'NA'
## Warning: Expecting numeric in O99 / R99C15: got 'NA'
## Warning: Expecting numeric in R99 / R99C18: got 'NA'
## Warning: Expecting numeric in S99 / R99C19: got 'NA'
## Warning: Expecting numeric in T99 / R99C20: got 'NA'
## Warning: Expecting numeric in AY99 / R99C51: got 'NA'
## Warning: Expecting numeric in G100 / R100C7: got 'NA'
## Warning: Expecting numeric in M100 / R100C13: got 'NA'
## Warning: Expecting numeric in N100 / R100C14: got 'NA'
## Warning: Expecting numeric in O100 / R100C15: got 'NA'
## Warning: Expecting numeric in R100 / R100C18: got 'NA'
## Warning: Expecting numeric in S100 / R100C19: got 'NA'
## Warning: Expecting numeric in T100 / R100C20: got 'NA'
## Warning: Expecting numeric in AY100 / R100C51: got 'NA'
## Warning: Expecting numeric in G101 / R101C7: got 'NA'
## Warning: Expecting numeric in M101 / R101C13: got 'NA'
## Warning: Expecting numeric in N101 / R101C14: got 'NA'
## Warning: Expecting numeric in O101 / R101C15: got 'NA'
## Warning: Expecting numeric in R101 / R101C18: got 'NA'
## Warning: Expecting numeric in S101 / R101C19: got 'NA'
## Warning: Expecting numeric in T101 / R101C20: got 'NA'
## Warning: Expecting numeric in AY101 / R101C51: got 'NA'
## Warning: Expecting numeric in M102 / R102C13: got 'NA'
## Warning: Expecting numeric in N102 / R102C14: got 'NA'
## Warning: Expecting numeric in O102 / R102C15: got 'NA'
## Warning: Expecting numeric in R102 / R102C18: got 'NA'
## Warning: Expecting numeric in S102 / R102C19: got 'NA'
## Warning: Expecting numeric in T102 / R102C20: got 'NA'
## Warning: Expecting numeric in X102 / R102C24: got 'NA'
## Warning: Expecting numeric in AY102 / R102C51: got 'NA'
## Warning: Expecting numeric in M103 / R103C13: got 'NA'
## Warning: Expecting numeric in N103 / R103C14: got 'NA'
## Warning: Expecting numeric in O103 / R103C15: got 'NA'
## Warning: Expecting numeric in R103 / R103C18: got 'NA'
## Warning: Expecting numeric in S103 / R103C19: got 'NA'
## Warning: Expecting numeric in T103 / R103C20: got 'NA'
## Warning: Expecting numeric in X103 / R103C24: got 'NA'
## Warning: Expecting numeric in AY103 / R103C51: got 'NA'
## Warning: Expecting numeric in M104 / R104C13: got 'NA'
## Warning: Expecting numeric in N104 / R104C14: got 'NA'
## Warning: Expecting numeric in O104 / R104C15: got 'NA'
## Warning: Expecting numeric in R104 / R104C18: got 'NA'
## Warning: Expecting numeric in S104 / R104C19: got 'NA'
## Warning: Expecting numeric in T104 / R104C20: got 'NA'
## Warning: Expecting numeric in X104 / R104C24: got 'NA'
## Warning: Expecting numeric in AY104 / R104C51: got 'NA'
## Warning: Expecting numeric in M105 / R105C13: got 'NA'
## Warning: Expecting numeric in N105 / R105C14: got 'NA'
## Warning: Expecting numeric in O105 / R105C15: got 'NA'
## Warning: Expecting numeric in R105 / R105C18: got 'NA'
## Warning: Expecting numeric in S105 / R105C19: got 'NA'
## Warning: Expecting numeric in T105 / R105C20: got 'NA'
## Warning: Expecting numeric in X105 / R105C24: got 'NA'
## Warning: Expecting numeric in AT105 / R105C46: got 'NA'
## Warning: Expecting numeric in AU105 / R105C47: got 'NA'
## Warning: Expecting numeric in AV105 / R105C48: got '-'
## Warning: Expecting numeric in AY105 / R105C51: got 'NA'
## Warning: Expecting numeric in M106 / R106C13: got 'NA'
## Warning: Expecting numeric in N106 / R106C14: got 'NA'
## Warning: Expecting numeric in O106 / R106C15: got 'NA'
## Warning: Expecting numeric in R106 / R106C18: got 'NA'
## Warning: Expecting numeric in S106 / R106C19: got 'NA'
## Warning: Expecting numeric in T106 / R106C20: got 'NA'
## Warning: Expecting numeric in X106 / R106C24: got 'NA'
## Warning: Expecting numeric in AT106 / R106C46: got 'NA'
## Warning: Expecting numeric in AU106 / R106C47: got 'NA'
## Warning: Expecting numeric in AV106 / R106C48: got '-'
## Warning: Expecting numeric in AY106 / R106C51: got 'NA'
## Warning: Expecting numeric in M107 / R107C13: got 'NA'
## Warning: Expecting numeric in N107 / R107C14: got 'NA'
## Warning: Expecting numeric in O107 / R107C15: got 'NA'
## Warning: Expecting numeric in R107 / R107C18: got 'NA'
## Warning: Expecting numeric in S107 / R107C19: got 'NA'
## Warning: Expecting numeric in T107 / R107C20: got 'NA'
## Warning: Expecting numeric in AY107 / R107C51: got 'NA'
## Warning: Expecting numeric in M108 / R108C13: got 'NA'
## Warning: Expecting numeric in N108 / R108C14: got 'NA'
## Warning: Expecting numeric in O108 / R108C15: got 'NA'
## Warning: Expecting numeric in R108 / R108C18: got 'NA'
## Warning: Expecting numeric in S108 / R108C19: got 'NA'
## Warning: Expecting numeric in T108 / R108C20: got 'NA'
## Warning: Expecting numeric in AY108 / R108C51: got 'NA'
## Warning: Expecting numeric in M109 / R109C13: got 'NA'
## Warning: Expecting numeric in N109 / R109C14: got 'NA'
## Warning: Expecting numeric in O109 / R109C15: got 'NA'
## Warning: Expecting numeric in R109 / R109C18: got 'NA'
## Warning: Expecting numeric in S109 / R109C19: got 'NA'
## Warning: Expecting numeric in T109 / R109C20: got 'NA'
## Warning: Expecting numeric in AY109 / R109C51: got 'NA'
## Warning: Expecting numeric in M110 / R110C13: got 'NA'
## Warning: Expecting numeric in N110 / R110C14: got 'NA'
## Warning: Expecting numeric in O110 / R110C15: got 'NA'
## Warning: Expecting numeric in R110 / R110C18: got 'NA'
## Warning: Expecting numeric in S110 / R110C19: got 'NA'
## Warning: Expecting numeric in T110 / R110C20: got 'NA'
## Warning: Expecting numeric in X110 / R110C24: got 'NA'
## Warning: Expecting numeric in AY110 / R110C51: got 'NA'
## Warning: Expecting numeric in M111 / R111C13: got 'NA'
## Warning: Expecting numeric in N111 / R111C14: got 'NA'
## Warning: Expecting numeric in O111 / R111C15: got 'NA'
## Warning: Expecting numeric in R111 / R111C18: got 'NA'
## Warning: Expecting numeric in S111 / R111C19: got 'NA'
## Warning: Expecting numeric in T111 / R111C20: got 'NA'
## Warning: Expecting numeric in AT111 / R111C46: got 'NA'
## Warning: Expecting numeric in AU111 / R111C47: got 'NA'
## Warning: Expecting numeric in AY111 / R111C51: got 'NA'
## Warning: Expecting numeric in M112 / R112C13: got 'NA'
## Warning: Expecting numeric in N112 / R112C14: got 'NA'
## Warning: Expecting numeric in O112 / R112C15: got 'NA'
## Warning: Expecting numeric in R112 / R112C18: got 'NA'
## Warning: Expecting numeric in S112 / R112C19: got 'NA'
## Warning: Expecting numeric in T112 / R112C20: got 'NA'
## Warning: Expecting numeric in AY112 / R112C51: got 'NA'
## Warning: Expecting numeric in M113 / R113C13: got 'NA'
## Warning: Expecting numeric in N113 / R113C14: got 'NA'
## Warning: Expecting numeric in O113 / R113C15: got 'NA'
## Warning: Expecting numeric in R113 / R113C18: got 'NA'
## Warning: Expecting numeric in S113 / R113C19: got 'NA'
## Warning: Expecting numeric in T113 / R113C20: got 'NA'
## Warning: Expecting numeric in AY113 / R113C51: got 'NA'
## Warning: Expecting numeric in M114 / R114C13: got 'NA'
## Warning: Expecting numeric in N114 / R114C14: got 'NA'
## Warning: Expecting numeric in O114 / R114C15: got 'NA'
## Warning: Expecting numeric in R114 / R114C18: got 'NA'
## Warning: Expecting numeric in S114 / R114C19: got 'NA'
## Warning: Expecting numeric in T114 / R114C20: got 'NA'
## Warning: Expecting numeric in AY114 / R114C51: got 'NA'
## Warning: Expecting numeric in M115 / R115C13: got 'NA'
## Warning: Expecting numeric in N115 / R115C14: got 'NA'
## Warning: Expecting numeric in O115 / R115C15: got 'NA'
## Warning: Expecting numeric in R115 / R115C18: got 'NA'
## Warning: Expecting numeric in S115 / R115C19: got 'NA'
## Warning: Expecting numeric in T115 / R115C20: got 'NA'
## Warning: Expecting numeric in AT115 / R115C46: got 'NA'
## Warning: Expecting numeric in AU115 / R115C47: got 'NA'
## Warning: Expecting numeric in AV115 / R115C48: got '-'
## Warning: Expecting numeric in AY115 / R115C51: got 'NA'
## Warning: Expecting numeric in M116 / R116C13: got 'NA'
## Warning: Expecting numeric in N116 / R116C14: got 'NA'
## Warning: Expecting numeric in O116 / R116C15: got 'NA'
## Warning: Expecting numeric in R116 / R116C18: got 'NA'
## Warning: Expecting numeric in S116 / R116C19: got 'NA'
## Warning: Expecting numeric in T116 / R116C20: got 'NA'
## Warning: Expecting numeric in AY116 / R116C51: got 'NA'
## Warning: Expecting numeric in M117 / R117C13: got 'NA'
## Warning: Expecting numeric in N117 / R117C14: got 'NA'
## Warning: Expecting numeric in O117 / R117C15: got 'NA'
## Warning: Expecting numeric in R117 / R117C18: got 'NA'
## Warning: Expecting numeric in S117 / R117C19: got 'NA'
## Warning: Expecting numeric in T117 / R117C20: got 'NA'
## Warning: Expecting numeric in AY117 / R117C51: got 'NA'
## Warning: Expecting numeric in M118 / R118C13: got 'NA'
## Warning: Expecting numeric in N118 / R118C14: got 'NA'
## Warning: Expecting numeric in O118 / R118C15: got 'NA'
## Warning: Expecting numeric in R118 / R118C18: got 'NA'
## Warning: Expecting numeric in S118 / R118C19: got 'NA'
## Warning: Expecting numeric in T118 / R118C20: got 'NA'
## Warning: Expecting numeric in AY118 / R118C51: got 'NA'
## Warning: Expecting numeric in M119 / R119C13: got 'NA'
## Warning: Expecting numeric in N119 / R119C14: got 'NA'
## Warning: Expecting numeric in O119 / R119C15: got 'NA'
## Warning: Expecting numeric in R119 / R119C18: got 'NA'
## Warning: Expecting numeric in S119 / R119C19: got 'NA'
## Warning: Expecting numeric in T119 / R119C20: got 'NA'
## Warning: Expecting numeric in AY119 / R119C51: got 'NA'
## Warning: Expecting numeric in M120 / R120C13: got 'NA'
## Warning: Expecting numeric in N120 / R120C14: got 'NA'
## Warning: Expecting numeric in O120 / R120C15: got 'NA'
## Warning: Expecting numeric in R120 / R120C18: got 'NA'
## Warning: Expecting numeric in S120 / R120C19: got 'NA'
## Warning: Expecting numeric in T120 / R120C20: got 'NA'
## Warning: Expecting numeric in AY120 / R120C51: got 'NA'
## Warning: Expecting numeric in M121 / R121C13: got 'NA'
## Warning: Expecting numeric in N121 / R121C14: got 'NA'
## Warning: Expecting numeric in O121 / R121C15: got 'NA'
## Warning: Expecting numeric in R121 / R121C18: got 'NA'
## Warning: Expecting numeric in S121 / R121C19: got 'NA'
## Warning: Expecting numeric in T121 / R121C20: got 'NA'
## Warning: Expecting numeric in AY121 / R121C51: got 'NA'
## Warning: Expecting numeric in M122 / R122C13: got 'NA'
## Warning: Expecting numeric in N122 / R122C14: got 'NA'
## Warning: Expecting numeric in O122 / R122C15: got 'NA'
## Warning: Expecting numeric in R122 / R122C18: got 'NA'
## Warning: Expecting numeric in S122 / R122C19: got 'NA'
## Warning: Expecting numeric in T122 / R122C20: got 'NA'
## Warning: Expecting numeric in X122 / R122C24: got 'NA'
## Warning: Expecting numeric in AT122 / R122C46: got 'NA'
## Warning: Expecting numeric in AU122 / R122C47: got 'NA'
## Warning: Expecting numeric in AV122 / R122C48: got '-'
## Warning: Expecting numeric in AY122 / R122C51: got 'NA'
## Warning: Expecting numeric in M123 / R123C13: got 'NA'
## Warning: Expecting numeric in N123 / R123C14: got 'NA'
## Warning: Expecting numeric in O123 / R123C15: got 'NA'
## Warning: Expecting numeric in R123 / R123C18: got 'NA'
## Warning: Expecting numeric in S123 / R123C19: got 'NA'
## Warning: Expecting numeric in T123 / R123C20: got 'NA'
## Warning: Expecting numeric in AY123 / R123C51: got 'NA'
## Warning: Expecting numeric in M124 / R124C13: got 'NA'
## Warning: Expecting numeric in N124 / R124C14: got 'NA'
## Warning: Expecting numeric in O124 / R124C15: got 'NA'
## Warning: Expecting numeric in R124 / R124C18: got 'NA'
## Warning: Expecting numeric in S124 / R124C19: got 'NA'
## Warning: Expecting numeric in T124 / R124C20: got 'NA'
## Warning: Expecting numeric in AT124 / R124C46: got 'NA'
## Warning: Expecting numeric in AU124 / R124C47: got 'NA'
## Warning: Expecting numeric in AY124 / R124C51: got 'NA'
## Warning: Expecting numeric in M125 / R125C13: got 'NA'
## Warning: Expecting numeric in N125 / R125C14: got 'NA'
## Warning: Expecting numeric in O125 / R125C15: got 'NA'
## Warning: Expecting numeric in R125 / R125C18: got 'NA'
## Warning: Expecting numeric in S125 / R125C19: got 'NA'
## Warning: Expecting numeric in T125 / R125C20: got 'NA'
## Warning: Expecting numeric in AY125 / R125C51: got 'NA'
## Warning: Expecting numeric in M126 / R126C13: got 'NA'
## Warning: Expecting numeric in N126 / R126C14: got 'NA'
## Warning: Expecting numeric in O126 / R126C15: got 'NA'
## Warning: Expecting numeric in R126 / R126C18: got 'NA'
## Warning: Expecting numeric in S126 / R126C19: got 'NA'
## Warning: Expecting numeric in T126 / R126C20: got 'NA'
## Warning: Expecting numeric in AY126 / R126C51: got 'NA'
## Warning: Expecting numeric in M127 / R127C13: got 'NA'
## Warning: Expecting numeric in N127 / R127C14: got 'NA'
## Warning: Expecting numeric in O127 / R127C15: got 'NA'
## Warning: Expecting numeric in R127 / R127C18: got 'NA'
## Warning: Expecting numeric in S127 / R127C19: got 'NA'
## Warning: Expecting numeric in T127 / R127C20: got 'NA'
## Warning: Expecting numeric in AY127 / R127C51: got 'NA'
## Warning: Expecting numeric in M128 / R128C13: got 'NA'
## Warning: Expecting numeric in N128 / R128C14: got 'NA'
## Warning: Expecting numeric in O128 / R128C15: got 'NA'
## Warning: Expecting numeric in R128 / R128C18: got 'NA'
## Warning: Expecting numeric in S128 / R128C19: got 'NA'
## Warning: Expecting numeric in T128 / R128C20: got 'NA'
## Warning: Expecting numeric in AY128 / R128C51: got 'NA'
## Warning: Expecting numeric in M129 / R129C13: got 'NA'
## Warning: Expecting numeric in N129 / R129C14: got 'NA'
## Warning: Expecting numeric in O129 / R129C15: got 'NA'
## Warning: Expecting numeric in R129 / R129C18: got 'NA'
## Warning: Expecting numeric in S129 / R129C19: got 'NA'
## Warning: Expecting numeric in T129 / R129C20: got 'NA'
## Warning: Coercing text to numeric in U129 / R129C21: '9.16111111'
## Warning: Expecting numeric in X129 / R129C24: got 'NA'
## Warning: Expecting numeric in AT129 / R129C46: got 'NA'
## Warning: Expecting numeric in AU129 / R129C47: got 'NA'
## Warning: Expecting numeric in AY129 / R129C51: got 'NA'
## Warning: Expecting numeric in M130 / R130C13: got 'NA'
## Warning: Expecting numeric in N130 / R130C14: got 'NA'
## Warning: Expecting numeric in O130 / R130C15: got 'NA'
## Warning: Expecting numeric in R130 / R130C18: got 'NA'
## Warning: Expecting numeric in S130 / R130C19: got 'NA'
## Warning: Expecting numeric in T130 / R130C20: got 'NA'
## Warning: Coercing text to numeric in U130 / R130C21: '9.16111111'
## Warning: Expecting numeric in X130 / R130C24: got 'NA'
## Warning: Expecting numeric in AY130 / R130C51: got 'NA'
## Warning: Expecting numeric in M131 / R131C13: got 'NA'
## Warning: Expecting numeric in N131 / R131C14: got 'NA'
## Warning: Expecting numeric in O131 / R131C15: got 'NA'
## Warning: Expecting numeric in R131 / R131C18: got 'NA'
## Warning: Expecting numeric in S131 / R131C19: got 'NA'
## Warning: Expecting numeric in T131 / R131C20: got 'NA'
## Warning: Coercing text to numeric in U131 / R131C21: '9.16111111'
## Warning: Expecting numeric in X131 / R131C24: got 'NA'
## Warning: Expecting numeric in AY131 / R131C51: got 'NA'
## Warning: Expecting numeric in M132 / R132C13: got 'NA'
## Warning: Expecting numeric in N132 / R132C14: got 'NA'
## Warning: Expecting numeric in O132 / R132C15: got 'NA'
## Warning: Expecting numeric in R132 / R132C18: got 'NA'
## Warning: Expecting numeric in S132 / R132C19: got 'NA'
## Warning: Expecting numeric in T132 / R132C20: got 'NA'
## Warning: Coercing text to numeric in U132 / R132C21: '9.16111111'
## Warning: Expecting numeric in X132 / R132C24: got 'NA'
## Warning: Expecting numeric in AY132 / R132C51: got 'NA'
## Warning: Expecting numeric in M133 / R133C13: got 'NA'
## Warning: Expecting numeric in N133 / R133C14: got 'NA'
## Warning: Expecting numeric in O133 / R133C15: got 'NA'
## Warning: Expecting numeric in R133 / R133C18: got 'NA'
## Warning: Expecting numeric in S133 / R133C19: got 'NA'
## Warning: Expecting numeric in T133 / R133C20: got 'NA'
## Warning: Expecting numeric in X133 / R133C24: got 'NA'
## Warning: Expecting numeric in AY133 / R133C51: got 'NA'
## Warning: Expecting numeric in M134 / R134C13: got 'NA'
## Warning: Expecting numeric in N134 / R134C14: got 'NA'
## Warning: Expecting numeric in O134 / R134C15: got 'NA'
## Warning: Expecting numeric in R134 / R134C18: got 'NA'
## Warning: Expecting numeric in S134 / R134C19: got 'NA'
## Warning: Expecting numeric in T134 / R134C20: got 'NA'
## Warning: Expecting numeric in X134 / R134C24: got 'NA'
## Warning: Expecting numeric in AY134 / R134C51: got 'NA'
## Warning: Expecting numeric in M135 / R135C13: got 'NA'
## Warning: Expecting numeric in N135 / R135C14: got 'NA'
## Warning: Expecting numeric in O135 / R135C15: got 'NA'
## Warning: Expecting numeric in R135 / R135C18: got 'NA'
## Warning: Expecting numeric in S135 / R135C19: got 'NA'
## Warning: Expecting numeric in T135 / R135C20: got 'NA'
## Warning: Expecting numeric in X135 / R135C24: got 'NA'
## Warning: Expecting numeric in AY135 / R135C51: got 'NA'
## Warning: Expecting numeric in M136 / R136C13: got 'NA'
## Warning: Expecting numeric in N136 / R136C14: got 'NA'
## Warning: Expecting numeric in O136 / R136C15: got 'NA'
## Warning: Expecting numeric in R136 / R136C18: got 'NA'
## Warning: Expecting numeric in S136 / R136C19: got 'NA'
## Warning: Expecting numeric in T136 / R136C20: got 'NA'
## Warning: Expecting numeric in X136 / R136C24: got 'NA'
## Warning: Expecting numeric in AY136 / R136C51: got 'NA'
## Warning: Expecting numeric in M137 / R137C13: got 'NA'
## Warning: Expecting numeric in N137 / R137C14: got 'NA'
## Warning: Expecting numeric in O137 / R137C15: got 'NA'
## Warning: Expecting numeric in R137 / R137C18: got 'NA'
## Warning: Expecting numeric in S137 / R137C19: got 'NA'
## Warning: Expecting numeric in T137 / R137C20: got 'NA'
## Warning: Expecting numeric in X137 / R137C24: got 'NA'
## Warning: Expecting numeric in AT137 / R137C46: got 'NA'
## Warning: Expecting numeric in AU137 / R137C47: got 'NA'
## Warning: Expecting numeric in AY137 / R137C51: got 'NA'
## Warning: Expecting numeric in M138 / R138C13: got 'NA'
## Warning: Expecting numeric in N138 / R138C14: got 'NA'
## Warning: Expecting numeric in O138 / R138C15: got 'NA'
## Warning: Expecting numeric in R138 / R138C18: got 'NA'
## Warning: Expecting numeric in S138 / R138C19: got 'NA'
## Warning: Expecting numeric in T138 / R138C20: got 'NA'
## Warning: Expecting numeric in X138 / R138C24: got 'NA'
## Warning: Expecting numeric in AY138 / R138C51: got 'NA'
## Warning: Expecting numeric in M139 / R139C13: got 'NA'
## Warning: Expecting numeric in N139 / R139C14: got 'NA'
## Warning: Expecting numeric in O139 / R139C15: got 'NA'
## Warning: Expecting numeric in R139 / R139C18: got 'NA'
## Warning: Expecting numeric in S139 / R139C19: got 'NA'
## Warning: Expecting numeric in T139 / R139C20: got 'NA'
## Warning: Expecting numeric in X139 / R139C24: got 'NA'
## Warning: Expecting numeric in AY139 / R139C51: got 'NA'
## Warning: Expecting numeric in M140 / R140C13: got 'NA'
## Warning: Expecting numeric in N140 / R140C14: got 'NA'
## Warning: Expecting numeric in O140 / R140C15: got 'NA'
## Warning: Expecting numeric in R140 / R140C18: got 'NA'
## Warning: Expecting numeric in S140 / R140C19: got 'NA'
## Warning: Expecting numeric in T140 / R140C20: got 'NA'
## Warning: Expecting numeric in AT140 / R140C46: got 'NA'
## Warning: Expecting numeric in AY140 / R140C51: got 'NA'
## Warning: Expecting numeric in M141 / R141C13: got 'NA'
## Warning: Expecting numeric in N141 / R141C14: got 'NA'
## Warning: Expecting numeric in O141 / R141C15: got 'NA'
## Warning: Expecting numeric in R141 / R141C18: got 'NA'
## Warning: Expecting numeric in S141 / R141C19: got 'NA'
## Warning: Expecting numeric in T141 / R141C20: got 'NA'
## Warning: Expecting numeric in AU141 / R141C47: got 'NA'
## Warning: Expecting numeric in AV141 / R141C48: got 'NA'
## Warning: Expecting numeric in AY141 / R141C51: got 'NA'
## Warning: Expecting numeric in M142 / R142C13: got 'NA'
## Warning: Expecting numeric in N142 / R142C14: got 'NA'
## Warning: Expecting numeric in O142 / R142C15: got 'NA'
## Warning: Expecting numeric in R142 / R142C18: got 'NA'
## Warning: Expecting numeric in S142 / R142C19: got 'NA'
## Warning: Expecting numeric in T142 / R142C20: got 'NA'
## Warning: Expecting numeric in AY142 / R142C51: got 'NA'
## Warning: Expecting numeric in M143 / R143C13: got 'NA'
## Warning: Expecting numeric in N143 / R143C14: got 'NA'
## Warning: Expecting numeric in O143 / R143C15: got 'NA'
## Warning: Expecting numeric in R143 / R143C18: got 'NA'
## Warning: Expecting numeric in S143 / R143C19: got 'NA'
## Warning: Expecting numeric in T143 / R143C20: got 'NA'
## Warning: Expecting numeric in AY143 / R143C51: got 'NA'
## Warning: Expecting numeric in M144 / R144C13: got 'NA'
## Warning: Expecting numeric in N144 / R144C14: got 'NA'
## Warning: Expecting numeric in O144 / R144C15: got 'NA'
## Warning: Expecting numeric in R144 / R144C18: got 'NA'
## Warning: Expecting numeric in S144 / R144C19: got 'NA'
## Warning: Expecting numeric in T144 / R144C20: got 'NA'
## Warning: Expecting numeric in AU144 / R144C47: got 'NA'
## Warning: Expecting numeric in AY144 / R144C51: got 'NA'
## Warning: Expecting numeric in M145 / R145C13: got 'NA'
## Warning: Expecting numeric in N145 / R145C14: got 'NA'
## Warning: Expecting numeric in O145 / R145C15: got 'NA'
## Warning: Expecting numeric in R145 / R145C18: got 'NA'
## Warning: Expecting numeric in S145 / R145C19: got 'NA'
## Warning: Expecting numeric in T145 / R145C20: got 'NA'
## Warning: Expecting numeric in AU145 / R145C47: got 'NA'
## Warning: Expecting numeric in AY145 / R145C51: got 'NA'
## Warning: Expecting numeric in M146 / R146C13: got 'NA'
## Warning: Expecting numeric in N146 / R146C14: got 'NA'
## Warning: Expecting numeric in O146 / R146C15: got 'NA'
## Warning: Expecting numeric in R146 / R146C18: got 'NA'
## Warning: Expecting numeric in S146 / R146C19: got 'NA'
## Warning: Expecting numeric in T146 / R146C20: got 'NA'
## Warning: Expecting numeric in AU146 / R146C47: got 'NA'
## Warning: Expecting numeric in AY146 / R146C51: got 'NA'
## Warning: Expecting numeric in M147 / R147C13: got 'NA'
## Warning: Expecting numeric in N147 / R147C14: got 'NA'
## Warning: Expecting numeric in O147 / R147C15: got 'NA'
## Warning: Expecting numeric in R147 / R147C18: got 'NA'
## Warning: Expecting numeric in S147 / R147C19: got 'NA'
## Warning: Expecting numeric in T147 / R147C20: got 'NA'
## Warning: Expecting numeric in AU147 / R147C47: got 'NA'
## Warning: Expecting numeric in AY147 / R147C51: got 'NA'
## Warning: Expecting numeric in M148 / R148C13: got 'NA'
## Warning: Expecting numeric in N148 / R148C14: got 'NA'
## Warning: Expecting numeric in O148 / R148C15: got 'NA'
## Warning: Expecting numeric in R148 / R148C18: got 'NA'
## Warning: Expecting numeric in S148 / R148C19: got 'NA'
## Warning: Expecting numeric in T148 / R148C20: got 'NA'
## Warning: Expecting numeric in AU148 / R148C47: got 'NA'
## Warning: Expecting numeric in AY148 / R148C51: got 'NA'
## Warning: Expecting numeric in M149 / R149C13: got 'NA'
## Warning: Expecting numeric in N149 / R149C14: got 'NA'
## Warning: Expecting numeric in O149 / R149C15: got 'NA'
## Warning: Expecting numeric in R149 / R149C18: got 'NA'
## Warning: Expecting numeric in S149 / R149C19: got 'NA'
## Warning: Expecting numeric in T149 / R149C20: got 'NA'
## Warning: Expecting numeric in AU149 / R149C47: got 'NA'
## Warning: Expecting numeric in AY149 / R149C51: got 'NA'
## Warning: Expecting numeric in M150 / R150C13: got 'NA'
## Warning: Expecting numeric in N150 / R150C14: got 'NA'
## Warning: Expecting numeric in O150 / R150C15: got 'NA'
## Warning: Expecting numeric in R150 / R150C18: got 'NA'
## Warning: Expecting numeric in S150 / R150C19: got 'NA'
## Warning: Expecting numeric in T150 / R150C20: got 'NA'
## Warning: Expecting numeric in AU150 / R150C47: got 'NA'
## Warning: Expecting numeric in AY150 / R150C51: got 'NA'
## Warning: Expecting numeric in M151 / R151C13: got 'NA'
## Warning: Expecting numeric in N151 / R151C14: got 'NA'
## Warning: Expecting numeric in O151 / R151C15: got 'NA'
## Warning: Expecting numeric in R151 / R151C18: got 'NA'
## Warning: Expecting numeric in S151 / R151C19: got 'NA'
## Warning: Expecting numeric in T151 / R151C20: got 'NA'
## Warning: Expecting numeric in AU151 / R151C47: got 'NA'
## Warning: Expecting numeric in AY151 / R151C51: got 'NA'
## Warning: Expecting numeric in M152 / R152C13: got 'NA'
## Warning: Expecting numeric in N152 / R152C14: got 'NA'
## Warning: Expecting numeric in O152 / R152C15: got 'NA'
## Warning: Expecting numeric in R152 / R152C18: got 'NA'
## Warning: Expecting numeric in S152 / R152C19: got 'NA'
## Warning: Expecting numeric in T152 / R152C20: got 'NA'
## Warning: Expecting numeric in AU152 / R152C47: got 'NA'
## Warning: Expecting numeric in AY152 / R152C51: got 'NA'
## Warning: Expecting numeric in M153 / R153C13: got 'NA'
## Warning: Expecting numeric in N153 / R153C14: got 'NA'
## Warning: Expecting numeric in O153 / R153C15: got 'NA'
## Warning: Expecting numeric in R153 / R153C18: got 'NA'
## Warning: Expecting numeric in S153 / R153C19: got 'NA'
## Warning: Expecting numeric in T153 / R153C20: got 'NA'
## Warning: Expecting numeric in AU153 / R153C47: got 'NA'
## Warning: Expecting numeric in AY153 / R153C51: got 'NA'
## Warning: Expecting numeric in M154 / R154C13: got 'NA'
## Warning: Expecting numeric in N154 / R154C14: got 'NA'
## Warning: Expecting numeric in O154 / R154C15: got 'NA'
## Warning: Expecting numeric in R154 / R154C18: got 'NA'
## Warning: Expecting numeric in S154 / R154C19: got 'NA'
## Warning: Expecting numeric in T154 / R154C20: got 'NA'
## Warning: Expecting numeric in X154 / R154C24: got 'NA'
## Warning: Expecting numeric in AY154 / R154C51: got 'NA'
## Warning: Expecting numeric in M155 / R155C13: got 'NA'
## Warning: Expecting numeric in N155 / R155C14: got 'NA'
## Warning: Expecting numeric in O155 / R155C15: got 'NA'
## Warning: Expecting numeric in R155 / R155C18: got 'NA'
## Warning: Expecting numeric in S155 / R155C19: got 'NA'
## Warning: Expecting numeric in T155 / R155C20: got 'NA'
## Warning: Expecting numeric in X155 / R155C24: got 'NA'
## Warning: Expecting numeric in AY155 / R155C51: got 'NA'
## Warning: Expecting numeric in M156 / R156C13: got 'NA'
## Warning: Expecting numeric in N156 / R156C14: got 'NA'
## Warning: Expecting numeric in O156 / R156C15: got 'NA'
## Warning: Expecting numeric in R156 / R156C18: got 'NA'
## Warning: Expecting numeric in S156 / R156C19: got 'NA'
## Warning: Expecting numeric in T156 / R156C20: got 'NA'
## Warning: Expecting numeric in AY156 / R156C51: got 'NA'
## Warning: Expecting numeric in M157 / R157C13: got 'NA'
## Warning: Expecting numeric in N157 / R157C14: got 'NA'
## Warning: Expecting numeric in O157 / R157C15: got 'NA'
## Warning: Expecting numeric in R157 / R157C18: got 'NA'
## Warning: Expecting numeric in S157 / R157C19: got 'NA'
## Warning: Expecting numeric in T157 / R157C20: got 'NA'
## Warning: Expecting numeric in AY157 / R157C51: got 'NA'
## Warning: Expecting numeric in M158 / R158C13: got 'NA'
## Warning: Expecting numeric in N158 / R158C14: got 'NA'
## Warning: Expecting numeric in O158 / R158C15: got 'NA'
## Warning: Expecting numeric in R158 / R158C18: got 'NA'
## Warning: Expecting numeric in S158 / R158C19: got 'NA'
## Warning: Expecting numeric in T158 / R158C20: got 'NA'
## Warning: Expecting numeric in AY158 / R158C51: got 'NA'
## Warning: Expecting numeric in M159 / R159C13: got 'NA'
## Warning: Expecting numeric in N159 / R159C14: got 'NA'
## Warning: Expecting numeric in O159 / R159C15: got 'NA'
## Warning: Expecting numeric in R159 / R159C18: got 'NA'
## Warning: Expecting numeric in S159 / R159C19: got 'NA'
## Warning: Expecting numeric in T159 / R159C20: got 'NA'
## Warning: Expecting numeric in AY159 / R159C51: got 'NA'
## Warning: Expecting numeric in M160 / R160C13: got 'NA'
## Warning: Expecting numeric in N160 / R160C14: got 'NA'
## Warning: Expecting numeric in O160 / R160C15: got 'NA'
## Warning: Expecting numeric in R160 / R160C18: got 'NA'
## Warning: Expecting numeric in S160 / R160C19: got 'NA'
## Warning: Expecting numeric in T160 / R160C20: got 'NA'
## Warning: Expecting numeric in AY160 / R160C51: got 'NA'
## Warning: Expecting numeric in M161 / R161C13: got 'NA'
## Warning: Expecting numeric in N161 / R161C14: got 'NA'
## Warning: Expecting numeric in O161 / R161C15: got 'NA'
## Warning: Expecting numeric in R161 / R161C18: got 'NA'
## Warning: Expecting numeric in S161 / R161C19: got 'NA'
## Warning: Expecting numeric in T161 / R161C20: got 'NA'
## Warning: Expecting numeric in AY161 / R161C51: got 'NA'
## Warning: Expecting numeric in M162 / R162C13: got 'NA'
## Warning: Expecting numeric in N162 / R162C14: got 'NA'
## Warning: Expecting numeric in O162 / R162C15: got 'NA'
## Warning: Expecting numeric in R162 / R162C18: got 'NA'
## Warning: Expecting numeric in S162 / R162C19: got 'NA'
## Warning: Expecting numeric in T162 / R162C20: got 'NA'
## Warning: Expecting numeric in AY162 / R162C51: got 'NA'
## Warning: Expecting numeric in M163 / R163C13: got 'NA'
## Warning: Expecting numeric in N163 / R163C14: got 'NA'
## Warning: Expecting numeric in O163 / R163C15: got 'NA'
## Warning: Expecting numeric in R163 / R163C18: got 'NA'
## Warning: Expecting numeric in S163 / R163C19: got 'NA'
## Warning: Expecting numeric in T163 / R163C20: got 'NA'
## Warning: Expecting numeric in AY163 / R163C51: got 'NA'
## Warning: Expecting numeric in M164 / R164C13: got 'NA'
## Warning: Expecting numeric in N164 / R164C14: got 'NA'
## Warning: Expecting numeric in O164 / R164C15: got 'NA'
## Warning: Expecting numeric in R164 / R164C18: got 'NA'
## Warning: Expecting numeric in S164 / R164C19: got 'NA'
## Warning: Expecting numeric in T164 / R164C20: got 'NA'
## Warning: Expecting numeric in AY164 / R164C51: got 'NA'
## Warning: Expecting numeric in M165 / R165C13: got 'NA'
## Warning: Expecting numeric in N165 / R165C14: got 'NA'
## Warning: Expecting numeric in O165 / R165C15: got 'NA'
## Warning: Expecting numeric in R165 / R165C18: got 'NA'
## Warning: Expecting numeric in S165 / R165C19: got 'NA'
## Warning: Expecting numeric in T165 / R165C20: got 'NA'
## Warning: Expecting numeric in AY165 / R165C51: got 'NA'
## Warning: Expecting numeric in M166 / R166C13: got 'NA'
## Warning: Expecting numeric in N166 / R166C14: got 'NA'
## Warning: Expecting numeric in O166 / R166C15: got 'NA'
## Warning: Expecting numeric in R166 / R166C18: got 'NA'
## Warning: Expecting numeric in S166 / R166C19: got 'NA'
## Warning: Expecting numeric in T166 / R166C20: got 'NA'
## Warning: Expecting numeric in AY166 / R166C51: got 'NA'
## Warning: Expecting numeric in M167 / R167C13: got 'NA'
## Warning: Expecting numeric in N167 / R167C14: got 'NA'
## Warning: Expecting numeric in O167 / R167C15: got 'NA'
## Warning: Expecting numeric in R167 / R167C18: got 'NA'
## Warning: Expecting numeric in S167 / R167C19: got 'NA'
## Warning: Expecting numeric in T167 / R167C20: got 'NA'
## Warning: Expecting numeric in AY167 / R167C51: got 'NA'
## Warning: Expecting numeric in M168 / R168C13: got 'NA'
## Warning: Expecting numeric in N168 / R168C14: got 'NA'
## Warning: Expecting numeric in O168 / R168C15: got 'NA'
## Warning: Expecting numeric in R168 / R168C18: got 'NA'
## Warning: Expecting numeric in S168 / R168C19: got 'NA'
## Warning: Expecting numeric in T168 / R168C20: got 'NA'
## Warning: Expecting numeric in AY168 / R168C51: got 'NA'
## Warning: Expecting numeric in M169 / R169C13: got 'NA'
## Warning: Expecting numeric in N169 / R169C14: got 'NA'
## Warning: Expecting numeric in O169 / R169C15: got 'NA'
## Warning: Expecting numeric in R169 / R169C18: got 'NA'
## Warning: Expecting numeric in S169 / R169C19: got 'NA'
## Warning: Expecting numeric in T169 / R169C20: got 'NA'
## Warning: Expecting numeric in AY169 / R169C51: got 'NA'
## Warning: Expecting numeric in M170 / R170C13: got 'NA'
## Warning: Expecting numeric in N170 / R170C14: got 'NA'
## Warning: Expecting numeric in O170 / R170C15: got 'NA'
## Warning: Expecting numeric in R170 / R170C18: got 'NA'
## Warning: Expecting numeric in S170 / R170C19: got 'NA'
## Warning: Expecting numeric in T170 / R170C20: got 'NA'
## Warning: Expecting numeric in AY170 / R170C51: got 'NA'
## Warning: Expecting numeric in M171 / R171C13: got 'NA'
## Warning: Expecting numeric in N171 / R171C14: got 'NA'
## Warning: Expecting numeric in O171 / R171C15: got 'NA'
## Warning: Expecting numeric in R171 / R171C18: got 'NA'
## Warning: Expecting numeric in S171 / R171C19: got 'NA'
## Warning: Expecting numeric in T171 / R171C20: got 'NA'
## Warning: Expecting numeric in AY171 / R171C51: got 'NA'
## Warning: Expecting numeric in M172 / R172C13: got 'NA'
## Warning: Expecting numeric in N172 / R172C14: got 'NA'
## Warning: Expecting numeric in O172 / R172C15: got 'NA'
## Warning: Expecting numeric in R172 / R172C18: got 'NA'
## Warning: Expecting numeric in S172 / R172C19: got 'NA'
## Warning: Expecting numeric in T172 / R172C20: got 'NA'
## Warning: Expecting numeric in AY172 / R172C51: got 'NA'
## Warning: Expecting numeric in M173 / R173C13: got 'NA'
## Warning: Expecting numeric in N173 / R173C14: got 'NA'
## Warning: Expecting numeric in O173 / R173C15: got 'NA'
## Warning: Expecting numeric in R173 / R173C18: got 'NA'
## Warning: Expecting numeric in S173 / R173C19: got 'NA'
## Warning: Expecting numeric in T173 / R173C20: got 'NA'
## Warning: Expecting numeric in AY173 / R173C51: got 'NA'
## Warning: Expecting numeric in M174 / R174C13: got 'NA'
## Warning: Expecting numeric in N174 / R174C14: got 'NA'
## Warning: Expecting numeric in O174 / R174C15: got 'NA'
## Warning: Expecting numeric in R174 / R174C18: got 'NA'
## Warning: Expecting numeric in S174 / R174C19: got 'NA'
## Warning: Expecting numeric in T174 / R174C20: got 'NA'
## Warning: Expecting numeric in AY174 / R174C51: got 'NA'
## Warning: Expecting numeric in M175 / R175C13: got 'NA'
## Warning: Expecting numeric in N175 / R175C14: got 'NA'
## Warning: Expecting numeric in O175 / R175C15: got 'NA'
## Warning: Expecting numeric in R175 / R175C18: got 'NA'
## Warning: Expecting numeric in S175 / R175C19: got 'NA'
## Warning: Expecting numeric in T175 / R175C20: got 'NA'
## Warning: Expecting numeric in AY175 / R175C51: got 'NA'
## Warning: Expecting numeric in M176 / R176C13: got 'NA'
## Warning: Expecting numeric in N176 / R176C14: got 'NA'
## Warning: Expecting numeric in O176 / R176C15: got 'NA'
## Warning: Expecting numeric in R176 / R176C18: got 'NA'
## Warning: Expecting numeric in S176 / R176C19: got 'NA'
## Warning: Expecting numeric in T176 / R176C20: got 'NA'
## Warning: Expecting numeric in AY176 / R176C51: got 'NA'
## Warning: Expecting numeric in M177 / R177C13: got 'NA'
## Warning: Expecting numeric in N177 / R177C14: got 'NA'
## Warning: Expecting numeric in O177 / R177C15: got 'NA'
## Warning: Expecting numeric in R177 / R177C18: got 'NA'
## Warning: Expecting numeric in S177 / R177C19: got 'NA'
## Warning: Expecting numeric in T177 / R177C20: got 'NA'
## Warning: Expecting numeric in AU177 / R177C47: got 'NA'
## Warning: Expecting numeric in AY177 / R177C51: got 'NA'
## Warning: Expecting numeric in M178 / R178C13: got 'NA'
## Warning: Expecting numeric in N178 / R178C14: got 'NA'
## Warning: Expecting numeric in O178 / R178C15: got 'NA'
## Warning: Expecting numeric in R178 / R178C18: got 'NA'
## Warning: Expecting numeric in S178 / R178C19: got 'NA'
## Warning: Expecting numeric in T178 / R178C20: got 'NA'
## Warning: Expecting numeric in AU178 / R178C47: got 'NA'
## Warning: Expecting numeric in AY178 / R178C51: got 'NA'
## Warning: Expecting numeric in M179 / R179C13: got 'NA'
## Warning: Expecting numeric in N179 / R179C14: got 'NA'
## Warning: Expecting numeric in O179 / R179C15: got 'NA'
## Warning: Expecting numeric in R179 / R179C18: got 'NA'
## Warning: Expecting numeric in S179 / R179C19: got 'NA'
## Warning: Expecting numeric in T179 / R179C20: got 'NA'
## Warning: Expecting numeric in AU179 / R179C47: got 'NA'
## Warning: Expecting numeric in AY179 / R179C51: got 'NA'
## Warning: Expecting numeric in M180 / R180C13: got 'NA'
## Warning: Expecting numeric in N180 / R180C14: got 'NA'
## Warning: Expecting numeric in O180 / R180C15: got 'NA'
## Warning: Expecting numeric in R180 / R180C18: got 'NA'
## Warning: Expecting numeric in S180 / R180C19: got 'NA'
## Warning: Expecting numeric in T180 / R180C20: got 'NA'
## Warning: Expecting numeric in AU180 / R180C47: got 'NA'
## Warning: Expecting numeric in AY180 / R180C51: got 'NA'
## Warning: Expecting numeric in M181 / R181C13: got 'NA'
## Warning: Expecting numeric in N181 / R181C14: got 'NA'
## Warning: Expecting numeric in O181 / R181C15: got 'NA'
## Warning: Expecting numeric in R181 / R181C18: got 'NA'
## Warning: Expecting numeric in S181 / R181C19: got 'NA'
## Warning: Expecting numeric in T181 / R181C20: got 'NA'
## Warning: Expecting numeric in AS181 / R181C45: got 'NA'
## Warning: Expecting numeric in AT181 / R181C46: got 'NA'
## Warning: Expecting numeric in AU181 / R181C47: got 'NA'
## Warning: Expecting numeric in AY181 / R181C51: got 'NA'
## Warning: Expecting numeric in M182 / R182C13: got 'NA'
## Warning: Expecting numeric in N182 / R182C14: got 'NA'
## Warning: Expecting numeric in O182 / R182C15: got 'NA'
## Warning: Expecting numeric in R182 / R182C18: got 'NA'
## Warning: Expecting numeric in S182 / R182C19: got 'NA'
## Warning: Expecting numeric in T182 / R182C20: got 'NA'
## Warning: Expecting numeric in AS182 / R182C45: got 'NA'
## Warning: Expecting numeric in AT182 / R182C46: got 'NA'
## Warning: Expecting numeric in AU182 / R182C47: got 'NA'
## Warning: Expecting numeric in AY182 / R182C51: got 'NA'
## Warning: Expecting numeric in M183 / R183C13: got 'NA'
## Warning: Expecting numeric in N183 / R183C14: got 'NA'
## Warning: Expecting numeric in O183 / R183C15: got 'NA'
## Warning: Expecting numeric in R183 / R183C18: got 'NA'
## Warning: Expecting numeric in S183 / R183C19: got 'NA'
## Warning: Expecting numeric in T183 / R183C20: got 'NA'
## Warning: Expecting numeric in AS183 / R183C45: got 'NA'
## Warning: Expecting numeric in AT183 / R183C46: got 'NA'
## Warning: Expecting numeric in AU183 / R183C47: got 'NA'
## Warning: Expecting numeric in AY183 / R183C51: got 'NA'
## Warning: Expecting numeric in M184 / R184C13: got 'NA'
## Warning: Expecting numeric in N184 / R184C14: got 'NA'
## Warning: Expecting numeric in O184 / R184C15: got 'NA'
## Warning: Expecting numeric in R184 / R184C18: got 'NA'
## Warning: Expecting numeric in S184 / R184C19: got 'NA'
## Warning: Expecting numeric in T184 / R184C20: got 'NA'
## Warning: Expecting numeric in AT184 / R184C46: got 'NA'
## Warning: Expecting numeric in AU184 / R184C47: got 'NA'
## Warning: Expecting numeric in AV184 / R184C48: got '800g'
## Warning: Expecting numeric in AY184 / R184C51: got 'NA'
## Warning: Expecting numeric in M185 / R185C13: got 'NA'
## Warning: Expecting numeric in N185 / R185C14: got 'NA'
## Warning: Expecting numeric in O185 / R185C15: got 'NA'
## Warning: Expecting numeric in R185 / R185C18: got 'NA'
## Warning: Expecting numeric in S185 / R185C19: got 'NA'
## Warning: Expecting numeric in T185 / R185C20: got 'NA'
## Warning: Expecting numeric in AY185 / R185C51: got 'NA'
## Warning: Expecting numeric in M186 / R186C13: got 'NA'
## Warning: Expecting numeric in N186 / R186C14: got 'NA'
## Warning: Expecting numeric in O186 / R186C15: got 'NA'
## Warning: Expecting numeric in R186 / R186C18: got 'NA'
## Warning: Expecting numeric in S186 / R186C19: got 'NA'
## Warning: Expecting numeric in T186 / R186C20: got 'NA'
## Warning: Expecting numeric in AY186 / R186C51: got 'NA'
## Warning: Expecting numeric in M187 / R187C13: got 'NA'
## Warning: Expecting numeric in N187 / R187C14: got 'NA'
## Warning: Expecting numeric in O187 / R187C15: got 'NA'
## Warning: Expecting numeric in R187 / R187C18: got 'NA'
## Warning: Expecting numeric in S187 / R187C19: got 'NA'
## Warning: Expecting numeric in T187 / R187C20: got 'NA'
## Warning: Expecting numeric in AY187 / R187C51: got 'NA'
## Warning: Expecting numeric in M188 / R188C13: got 'NA'
## Warning: Expecting numeric in N188 / R188C14: got 'NA'
## Warning: Expecting numeric in O188 / R188C15: got 'NA'
## Warning: Expecting numeric in R188 / R188C18: got 'NA'
## Warning: Expecting numeric in S188 / R188C19: got 'NA'
## Warning: Expecting numeric in T188 / R188C20: got 'NA'
## Warning: Expecting numeric in X188 / R188C24: got 'NA'
## Warning: Expecting numeric in AY188 / R188C51: got 'NA'
## Warning: Expecting numeric in M189 / R189C13: got 'NA'
## Warning: Expecting numeric in N189 / R189C14: got 'NA'
## Warning: Expecting numeric in O189 / R189C15: got 'NA'
## Warning: Expecting numeric in R189 / R189C18: got 'NA'
## Warning: Expecting numeric in S189 / R189C19: got 'NA'
## Warning: Expecting numeric in T189 / R189C20: got 'NA'
## Warning: Expecting numeric in AT189 / R189C46: got 'NA'
## Warning: Expecting numeric in AV189 / R189C48: got 'NA'
## Warning: Expecting numeric in AY189 / R189C51: got 'NA'
## Warning: Expecting numeric in M190 / R190C13: got 'NA'
## Warning: Expecting numeric in N190 / R190C14: got 'NA'
## Warning: Expecting numeric in O190 / R190C15: got 'NA'
## Warning: Expecting numeric in R190 / R190C18: got 'NA'
## Warning: Expecting numeric in S190 / R190C19: got 'NA'
## Warning: Expecting numeric in T190 / R190C20: got 'NA'
## Warning: Expecting numeric in AY190 / R190C51: got 'NA'
## Warning: Expecting numeric in M191 / R191C13: got 'NA'
## Warning: Expecting numeric in N191 / R191C14: got 'NA'
## Warning: Expecting numeric in O191 / R191C15: got 'NA'
## Warning: Expecting numeric in R191 / R191C18: got 'NA'
## Warning: Expecting numeric in S191 / R191C19: got 'NA'
## Warning: Expecting numeric in T191 / R191C20: got 'NA'
## Warning: Expecting numeric in AY191 / R191C51: got 'NA'
## Warning: Expecting numeric in M192 / R192C13: got 'NA'
## Warning: Expecting numeric in N192 / R192C14: got 'NA'
## Warning: Expecting numeric in O192 / R192C15: got 'NA'
## Warning: Expecting numeric in R192 / R192C18: got 'NA'
## Warning: Expecting numeric in S192 / R192C19: got 'NA'
## Warning: Expecting numeric in T192 / R192C20: got 'NA'
## Warning: Expecting numeric in AY192 / R192C51: got 'NA'
## Warning: Expecting numeric in M193 / R193C13: got 'NA'
## Warning: Expecting numeric in N193 / R193C14: got 'NA'
## Warning: Expecting numeric in O193 / R193C15: got 'NA'
## Warning: Expecting numeric in R193 / R193C18: got 'NA'
## Warning: Expecting numeric in S193 / R193C19: got 'NA'
## Warning: Expecting numeric in T193 / R193C20: got 'NA'
## Warning: Expecting numeric in AY193 / R193C51: got 'NA'
## Warning: Expecting numeric in M194 / R194C13: got 'NA'
## Warning: Expecting numeric in N194 / R194C14: got 'NA'
## Warning: Expecting numeric in O194 / R194C15: got 'NA'
## Warning: Expecting numeric in R194 / R194C18: got 'NA'
## Warning: Expecting numeric in S194 / R194C19: got 'NA'
## Warning: Expecting numeric in T194 / R194C20: got 'NA'
## Warning: Expecting numeric in AY194 / R194C51: got 'NA'
## Warning: Expecting numeric in M195 / R195C13: got 'NA'
## Warning: Expecting numeric in N195 / R195C14: got 'NA'
## Warning: Expecting numeric in O195 / R195C15: got 'NA'
## Warning: Expecting numeric in R195 / R195C18: got 'NA'
## Warning: Expecting numeric in S195 / R195C19: got 'NA'
## Warning: Expecting numeric in T195 / R195C20: got 'NA'
## Warning: Expecting numeric in AY195 / R195C51: got 'NA'
## Warning: Expecting numeric in M196 / R196C13: got 'NA'
## Warning: Expecting numeric in N196 / R196C14: got 'NA'
## Warning: Expecting numeric in O196 / R196C15: got 'NA'
## Warning: Expecting numeric in R196 / R196C18: got 'NA'
## Warning: Expecting numeric in S196 / R196C19: got 'NA'
## Warning: Expecting numeric in T196 / R196C20: got 'NA'
## Warning: Expecting numeric in AY196 / R196C51: got 'NA'
## Warning: Expecting numeric in M197 / R197C13: got 'NA'
## Warning: Expecting numeric in N197 / R197C14: got 'NA'
## Warning: Expecting numeric in O197 / R197C15: got 'NA'
## Warning: Expecting numeric in R197 / R197C18: got 'NA'
## Warning: Expecting numeric in S197 / R197C19: got 'NA'
## Warning: Expecting numeric in T197 / R197C20: got 'NA'
## Warning: Expecting numeric in AY197 / R197C51: got 'NA'
## Warning: Expecting numeric in M198 / R198C13: got 'NA'
## Warning: Expecting numeric in N198 / R198C14: got 'NA'
## Warning: Expecting numeric in O198 / R198C15: got 'NA'
## Warning: Expecting numeric in R198 / R198C18: got 'NA'
## Warning: Expecting numeric in S198 / R198C19: got 'NA'
## Warning: Expecting numeric in T198 / R198C20: got 'NA'
## Warning: Expecting numeric in AY198 / R198C51: got 'NA'
## Warning: Expecting numeric in M199 / R199C13: got 'NA'
## Warning: Expecting numeric in N199 / R199C14: got 'NA'
## Warning: Expecting numeric in O199 / R199C15: got 'NA'
## Warning: Expecting numeric in R199 / R199C18: got 'NA'
## Warning: Expecting numeric in S199 / R199C19: got 'NA'
## Warning: Expecting numeric in T199 / R199C20: got 'NA'
## Warning: Expecting numeric in AY199 / R199C51: got 'NA'
## Warning: Expecting numeric in M200 / R200C13: got 'NA'
## Warning: Expecting numeric in N200 / R200C14: got 'NA'
## Warning: Expecting numeric in O200 / R200C15: got 'NA'
## Warning: Expecting numeric in R200 / R200C18: got 'NA'
## Warning: Expecting numeric in S200 / R200C19: got 'NA'
## Warning: Expecting numeric in T200 / R200C20: got 'NA'
## Warning: Expecting numeric in AY200 / R200C51: got 'NA'
## Warning: Expecting numeric in G201 / R201C7: got 'NA'
## Warning: Expecting numeric in M201 / R201C13: got 'NA'
## Warning: Expecting numeric in N201 / R201C14: got 'NA'
## Warning: Expecting numeric in O201 / R201C15: got 'NA'
## Warning: Expecting numeric in R201 / R201C18: got 'NA'
## Warning: Expecting numeric in S201 / R201C19: got 'NA'
## Warning: Expecting numeric in T201 / R201C20: got 'NA'
## Warning: Expecting numeric in X201 / R201C24: got 'NA'
## Warning: Expecting numeric in AY201 / R201C51: got 'NA'
## Warning: Expecting numeric in G202 / R202C7: got 'NA'
## Warning: Expecting numeric in M202 / R202C13: got 'NA'
## Warning: Expecting numeric in N202 / R202C14: got 'NA'
## Warning: Expecting numeric in O202 / R202C15: got 'NA'
## Warning: Expecting numeric in R202 / R202C18: got 'NA'
## Warning: Expecting numeric in S202 / R202C19: got 'NA'
## Warning: Expecting numeric in T202 / R202C20: got 'NA'
## Warning: Expecting numeric in X202 / R202C24: got 'NA'
## Warning: Expecting numeric in AY202 / R202C51: got 'NA'
## Warning: Expecting numeric in G203 / R203C7: got 'NA'
## Warning: Expecting numeric in M203 / R203C13: got 'NA'
## Warning: Expecting numeric in N203 / R203C14: got 'NA'
## Warning: Expecting numeric in O203 / R203C15: got 'NA'
## Warning: Expecting numeric in R203 / R203C18: got 'NA'
## Warning: Expecting numeric in S203 / R203C19: got 'NA'
## Warning: Expecting numeric in T203 / R203C20: got 'NA'
## Warning: Expecting numeric in X203 / R203C24: got 'NA'
## Warning: Expecting numeric in AY203 / R203C51: got 'NA'
## Warning: Expecting numeric in G204 / R204C7: got 'NA'
## Warning: Expecting numeric in M204 / R204C13: got 'NA'
## Warning: Expecting numeric in N204 / R204C14: got 'NA'
## Warning: Expecting numeric in O204 / R204C15: got 'NA'
## Warning: Expecting numeric in R204 / R204C18: got 'NA'
## Warning: Expecting numeric in S204 / R204C19: got 'NA'
## Warning: Expecting numeric in T204 / R204C20: got 'NA'
## Warning: Expecting numeric in X204 / R204C24: got 'NA'
## Warning: Expecting numeric in AY204 / R204C51: got 'NA'
## Warning: Expecting numeric in G205 / R205C7: got 'NA'
## Warning: Expecting numeric in M205 / R205C13: got 'NA'
## Warning: Expecting numeric in N205 / R205C14: got 'NA'
## Warning: Expecting numeric in O205 / R205C15: got 'NA'
## Warning: Expecting numeric in R205 / R205C18: got 'NA'
## Warning: Expecting numeric in S205 / R205C19: got 'NA'
## Warning: Expecting numeric in T205 / R205C20: got 'NA'
## Warning: Expecting numeric in X205 / R205C24: got 'NA'
## Warning: Expecting numeric in AY205 / R205C51: got 'NA'
## Warning: Expecting numeric in G206 / R206C7: got 'NA'
## Warning: Expecting numeric in M206 / R206C13: got 'NA'
## Warning: Expecting numeric in N206 / R206C14: got 'NA'
## Warning: Expecting numeric in O206 / R206C15: got 'NA'
## Warning: Expecting numeric in R206 / R206C18: got 'NA'
## Warning: Expecting numeric in S206 / R206C19: got 'NA'
## Warning: Expecting numeric in T206 / R206C20: got 'NA'
## Warning: Expecting numeric in X206 / R206C24: got 'NA'
## Warning: Expecting numeric in AY206 / R206C51: got 'NA'
## Warning: Expecting numeric in M207 / R207C13: got 'NA'
## Warning: Expecting numeric in N207 / R207C14: got 'NA'
## Warning: Expecting numeric in O207 / R207C15: got 'NA'
## Warning: Expecting numeric in R207 / R207C18: got 'NA'
## Warning: Expecting numeric in S207 / R207C19: got 'NA'
## Warning: Expecting numeric in T207 / R207C20: got 'NA'
## Warning: Expecting numeric in AS207 / R207C45: got 'NA'
## Warning: Expecting numeric in AT207 / R207C46: got 'NA'
## Warning: Expecting numeric in AV207 / R207C48: got 'NA'
## Warning: Expecting numeric in AY207 / R207C51: got 'NA'
## Warning: Expecting numeric in M208 / R208C13: got 'NA'
## Warning: Expecting numeric in N208 / R208C14: got 'NA'
## Warning: Expecting numeric in O208 / R208C15: got 'NA'
## Warning: Expecting numeric in R208 / R208C18: got 'NA'
## Warning: Expecting numeric in S208 / R208C19: got 'NA'
## Warning: Expecting numeric in T208 / R208C20: got 'NA'
## Warning: Expecting numeric in AS208 / R208C45: got 'NA'
## Warning: Expecting numeric in AT208 / R208C46: got 'NA'
## Warning: Expecting numeric in AY208 / R208C51: got 'NA'
## Warning: Expecting numeric in M209 / R209C13: got 'NA'
## Warning: Expecting numeric in N209 / R209C14: got 'NA'
## Warning: Expecting numeric in O209 / R209C15: got 'NA'
## Warning: Expecting numeric in R209 / R209C18: got 'NA'
## Warning: Expecting numeric in S209 / R209C19: got 'NA'
## Warning: Expecting numeric in T209 / R209C20: got 'NA'
## Warning: Expecting numeric in AS209 / R209C45: got 'NA'
## Warning: Expecting numeric in AT209 / R209C46: got 'NA'
## Warning: Expecting numeric in AY209 / R209C51: got 'NA'
## Warning: Expecting numeric in M210 / R210C13: got 'NA'
## Warning: Expecting numeric in N210 / R210C14: got 'NA'
## Warning: Expecting numeric in O210 / R210C15: got 'NA'
## Warning: Expecting numeric in R210 / R210C18: got 'NA'
## Warning: Expecting numeric in S210 / R210C19: got 'NA'
## Warning: Expecting numeric in T210 / R210C20: got 'NA'
## Warning: Expecting numeric in AY210 / R210C51: got 'NA'
## Warning: Expecting numeric in M211 / R211C13: got 'NA'
## Warning: Expecting numeric in N211 / R211C14: got 'NA'
## Warning: Expecting numeric in O211 / R211C15: got 'NA'
## Warning: Expecting numeric in R211 / R211C18: got 'NA'
## Warning: Expecting numeric in S211 / R211C19: got 'NA'
## Warning: Expecting numeric in T211 / R211C20: got 'NA'
## Warning: Expecting numeric in AY211 / R211C51: got 'NA'
## Warning: Expecting numeric in M212 / R212C13: got 'NA'
## Warning: Expecting numeric in N212 / R212C14: got 'NA'
## Warning: Expecting numeric in O212 / R212C15: got 'NA'
## Warning: Expecting numeric in R212 / R212C18: got 'NA'
## Warning: Expecting numeric in S212 / R212C19: got 'NA'
## Warning: Expecting numeric in T212 / R212C20: got 'NA'
## Warning: Expecting numeric in AY212 / R212C51: got 'NA'
## Warning: Expecting numeric in M213 / R213C13: got 'NA'
## Warning: Expecting numeric in N213 / R213C14: got 'NA'
## Warning: Expecting numeric in O213 / R213C15: got 'NA'
## Warning: Expecting numeric in R213 / R213C18: got 'NA'
## Warning: Expecting numeric in S213 / R213C19: got 'NA'
## Warning: Expecting numeric in T213 / R213C20: got 'NA'
## Warning: Expecting numeric in AY213 / R213C51: got 'NA'
## Warning: Expecting date in D214 / R214C4: got '23:06/2023'
## Warning: Expecting numeric in M214 / R214C13: got 'NA'
## Warning: Expecting numeric in N214 / R214C14: got 'NA'
## Warning: Expecting numeric in O214 / R214C15: got 'NA'
## Warning: Expecting numeric in R214 / R214C18: got 'NA'
## Warning: Expecting numeric in S214 / R214C19: got 'NA'
## Warning: Expecting numeric in T214 / R214C20: got 'NA'
## Warning: Expecting numeric in AY214 / R214C51: got 'NA'
## Warning: Expecting date in D215 / R215C4: got '23:06/2023'
## Warning: Expecting numeric in M215 / R215C13: got 'NA'
## Warning: Expecting numeric in N215 / R215C14: got 'NA'
## Warning: Expecting numeric in O215 / R215C15: got 'NA'
## Warning: Expecting numeric in R215 / R215C18: got 'NA'
## Warning: Expecting numeric in S215 / R215C19: got 'NA'
## Warning: Expecting numeric in T215 / R215C20: got 'NA'
## Warning: Expecting numeric in AY215 / R215C51: got 'NA'
## Warning: Expecting numeric in M216 / R216C13: got 'NA'
## Warning: Expecting numeric in N216 / R216C14: got 'NA'
## Warning: Expecting numeric in O216 / R216C15: got 'NA'
## Warning: Expecting numeric in R216 / R216C18: got 'NA'
## Warning: Expecting numeric in S216 / R216C19: got 'NA'
## Warning: Expecting numeric in T216 / R216C20: got 'NA'
## Warning: Expecting numeric in AY216 / R216C51: got 'NA'
## Warning: Expecting numeric in M217 / R217C13: got 'NA'
## Warning: Expecting numeric in N217 / R217C14: got 'NA'
## Warning: Expecting numeric in O217 / R217C15: got 'NA'
## Warning: Expecting numeric in R217 / R217C18: got 'NA'
## Warning: Expecting numeric in S217 / R217C19: got 'NA'
## Warning: Expecting numeric in T217 / R217C20: got 'NA'
## Warning: Expecting numeric in AY217 / R217C51: got 'NA'
## Warning: Expecting numeric in M218 / R218C13: got 'NA'
## Warning: Expecting numeric in N218 / R218C14: got 'NA'
## Warning: Expecting numeric in O218 / R218C15: got 'NA'
## Warning: Expecting numeric in R218 / R218C18: got 'NA'
## Warning: Expecting numeric in S218 / R218C19: got 'NA'
## Warning: Expecting numeric in T218 / R218C20: got 'NA'
## Warning: Expecting numeric in AY218 / R218C51: got 'NA'
## Warning: Expecting numeric in M219 / R219C13: got 'NA'
## Warning: Expecting numeric in N219 / R219C14: got 'NA'
## Warning: Expecting numeric in O219 / R219C15: got 'NA'
## Warning: Expecting numeric in R219 / R219C18: got 'NA'
## Warning: Expecting numeric in S219 / R219C19: got 'NA'
## Warning: Expecting numeric in T219 / R219C20: got 'NA'
## Warning: Expecting numeric in AY219 / R219C51: got 'NA'
## Warning: Expecting numeric in M220 / R220C13: got 'NA'
## Warning: Expecting numeric in N220 / R220C14: got 'NA'
## Warning: Expecting numeric in O220 / R220C15: got 'NA'
## Warning: Expecting numeric in R220 / R220C18: got 'NA'
## Warning: Expecting numeric in S220 / R220C19: got 'NA'
## Warning: Expecting numeric in T220 / R220C20: got 'NA'
## Warning: Expecting numeric in AY220 / R220C51: got 'NA'
## Warning: Expecting numeric in M221 / R221C13: got 'NA'
## Warning: Expecting numeric in N221 / R221C14: got 'NA'
## Warning: Expecting numeric in O221 / R221C15: got 'NA'
## Warning: Expecting numeric in R221 / R221C18: got 'NA'
## Warning: Expecting numeric in S221 / R221C19: got 'NA'
## Warning: Expecting numeric in T221 / R221C20: got 'NA'
## Warning: Expecting numeric in AY221 / R221C51: got 'NA'
## Warning: Expecting numeric in M222 / R222C13: got 'NA'
## Warning: Expecting numeric in N222 / R222C14: got 'NA'
## Warning: Expecting numeric in O222 / R222C15: got 'NA'
## Warning: Expecting numeric in R222 / R222C18: got 'NA'
## Warning: Expecting numeric in S222 / R222C19: got 'NA'
## Warning: Expecting numeric in T222 / R222C20: got 'NA'
## Warning: Expecting numeric in AY222 / R222C51: got 'NA'
## Warning: Expecting numeric in M223 / R223C13: got 'NA'
## Warning: Expecting numeric in N223 / R223C14: got 'NA'
## Warning: Expecting numeric in O223 / R223C15: got 'NA'
## Warning: Expecting numeric in R223 / R223C18: got 'NA'
## Warning: Expecting numeric in S223 / R223C19: got 'NA'
## Warning: Expecting numeric in T223 / R223C20: got 'NA'
## Warning: Expecting numeric in AY223 / R223C51: got 'NA'
## Warning: Expecting numeric in M224 / R224C13: got 'NA'
## Warning: Expecting numeric in N224 / R224C14: got 'NA'
## Warning: Expecting numeric in O224 / R224C15: got 'NA'
## Warning: Expecting numeric in R224 / R224C18: got 'NA'
## Warning: Expecting numeric in S224 / R224C19: got 'NA'
## Warning: Expecting numeric in T224 / R224C20: got 'NA'
## Warning: Expecting numeric in AV224 / R224C48: got 'NA'
## Warning: Expecting numeric in AY224 / R224C51: got 'NA'
## Warning: Expecting numeric in M225 / R225C13: got 'NA'
## Warning: Expecting numeric in N225 / R225C14: got 'NA'
## Warning: Expecting numeric in O225 / R225C15: got 'NA'
## Warning: Expecting numeric in R225 / R225C18: got 'NA'
## Warning: Expecting numeric in S225 / R225C19: got 'NA'
## Warning: Expecting numeric in T225 / R225C20: got 'NA'
## Warning: Expecting numeric in AY225 / R225C51: got 'NA'
## Warning: Expecting numeric in M226 / R226C13: got 'NA'
## Warning: Expecting numeric in N226 / R226C14: got 'NA'
## Warning: Expecting numeric in O226 / R226C15: got 'NA'
## Warning: Expecting numeric in R226 / R226C18: got 'NA'
## Warning: Expecting numeric in S226 / R226C19: got 'NA'
## Warning: Expecting numeric in T226 / R226C20: got 'NA'
## Warning: Expecting numeric in AY226 / R226C51: got 'NA'
## Warning: Expecting numeric in M227 / R227C13: got 'NA'
## Warning: Expecting numeric in N227 / R227C14: got 'NA'
## Warning: Expecting numeric in O227 / R227C15: got 'NA'
## Warning: Expecting numeric in R227 / R227C18: got 'NA'
## Warning: Expecting numeric in S227 / R227C19: got 'NA'
## Warning: Expecting numeric in T227 / R227C20: got 'NA'
## Warning: Expecting numeric in AY227 / R227C51: got 'NA'
## Warning: Expecting numeric in M228 / R228C13: got 'NA'
## Warning: Expecting numeric in N228 / R228C14: got 'NA'
## Warning: Expecting numeric in O228 / R228C15: got 'NA'
## Warning: Expecting numeric in R228 / R228C18: got 'NA'
## Warning: Expecting numeric in S228 / R228C19: got 'NA'
## Warning: Expecting numeric in T228 / R228C20: got 'NA'
## Warning: Expecting numeric in AY228 / R228C51: got 'NA'
## Warning: Expecting numeric in M229 / R229C13: got 'NA'
## Warning: Expecting numeric in N229 / R229C14: got 'NA'
## Warning: Expecting numeric in O229 / R229C15: got 'NA'
## Warning: Expecting numeric in R229 / R229C18: got 'NA'
## Warning: Expecting numeric in S229 / R229C19: got 'NA'
## Warning: Expecting numeric in T229 / R229C20: got 'NA'
## Warning: Expecting numeric in AY229 / R229C51: got 'NA'
## Warning: Expecting numeric in M230 / R230C13: got 'NA'
## Warning: Expecting numeric in N230 / R230C14: got 'NA'
## Warning: Expecting numeric in O230 / R230C15: got 'NA'
## Warning: Expecting numeric in R230 / R230C18: got 'NA'
## Warning: Expecting numeric in S230 / R230C19: got 'NA'
## Warning: Expecting numeric in T230 / R230C20: got 'NA'
## Warning: Expecting numeric in AY230 / R230C51: got 'NA'
## Warning: Expecting numeric in M231 / R231C13: got 'NA'
## Warning: Expecting numeric in N231 / R231C14: got 'NA'
## Warning: Expecting numeric in O231 / R231C15: got 'NA'
## Warning: Expecting numeric in R231 / R231C18: got 'NA'
## Warning: Expecting numeric in S231 / R231C19: got 'NA'
## Warning: Expecting numeric in T231 / R231C20: got 'NA'
## Warning: Expecting numeric in AY231 / R231C51: got 'NA'
## Warning: Expecting numeric in M232 / R232C13: got 'NA'
## Warning: Expecting numeric in N232 / R232C14: got 'NA'
## Warning: Expecting numeric in O232 / R232C15: got 'NA'
## Warning: Expecting numeric in R232 / R232C18: got 'NA'
## Warning: Expecting numeric in S232 / R232C19: got 'NA'
## Warning: Expecting numeric in T232 / R232C20: got 'NA'
## Warning: Expecting numeric in AY232 / R232C51: got 'NA'
## Warning: Expecting numeric in M233 / R233C13: got 'NA'
## Warning: Expecting numeric in N233 / R233C14: got 'NA'
## Warning: Expecting numeric in O233 / R233C15: got 'NA'
## Warning: Expecting numeric in R233 / R233C18: got 'NA'
## Warning: Expecting numeric in S233 / R233C19: got 'NA'
## Warning: Expecting numeric in T233 / R233C20: got 'NA'
## Warning: Expecting numeric in AY233 / R233C51: got 'NA'
## Warning: Expecting numeric in M234 / R234C13: got 'NA'
## Warning: Expecting numeric in N234 / R234C14: got 'NA'
## Warning: Expecting numeric in O234 / R234C15: got 'NA'
## Warning: Expecting numeric in R234 / R234C18: got 'NA'
## Warning: Expecting numeric in S234 / R234C19: got 'NA'
## Warning: Expecting numeric in T234 / R234C20: got 'NA'
## Warning: Expecting numeric in AY234 / R234C51: got 'NA'
## Warning: Expecting numeric in M235 / R235C13: got 'NA'
## Warning: Expecting numeric in N235 / R235C14: got 'NA'
## Warning: Expecting numeric in O235 / R235C15: got 'NA'
## Warning: Expecting numeric in R235 / R235C18: got 'NA'
## Warning: Expecting numeric in S235 / R235C19: got 'NA'
## Warning: Expecting numeric in T235 / R235C20: got 'NA'
## Warning: Expecting numeric in AY235 / R235C51: got 'NA'
## Warning: Expecting numeric in M236 / R236C13: got 'NA'
## Warning: Expecting numeric in N236 / R236C14: got 'NA'
## Warning: Expecting numeric in O236 / R236C15: got 'NA'
## Warning: Expecting numeric in R236 / R236C18: got 'NA'
## Warning: Expecting numeric in S236 / R236C19: got 'NA'
## Warning: Expecting numeric in T236 / R236C20: got 'NA'
## Warning: Expecting numeric in AY236 / R236C51: got 'NA'
## Warning: Expecting numeric in M237 / R237C13: got 'NA'
## Warning: Expecting numeric in N237 / R237C14: got 'NA'
## Warning: Expecting numeric in O237 / R237C15: got 'NA'
## Warning: Expecting numeric in R237 / R237C18: got 'NA'
## Warning: Expecting numeric in S237 / R237C19: got 'NA'
## Warning: Expecting numeric in T237 / R237C20: got 'NA'
## Warning: Expecting numeric in AY237 / R237C51: got 'NA'
## Warning: Expecting numeric in M238 / R238C13: got 'NA'
## Warning: Expecting numeric in N238 / R238C14: got 'NA'
## Warning: Expecting numeric in O238 / R238C15: got 'NA'
## Warning: Expecting numeric in R238 / R238C18: got 'NA'
## Warning: Expecting numeric in S238 / R238C19: got 'NA'
## Warning: Expecting numeric in T238 / R238C20: got 'NA'
## Warning: Expecting numeric in AY238 / R238C51: got 'NA'
## Warning: Expecting numeric in M239 / R239C13: got 'NA'
## Warning: Expecting numeric in N239 / R239C14: got 'NA'
## Warning: Expecting numeric in O239 / R239C15: got 'NA'
## Warning: Expecting numeric in R239 / R239C18: got 'NA'
## Warning: Expecting numeric in S239 / R239C19: got 'NA'
## Warning: Expecting numeric in T239 / R239C20: got 'NA'
## Warning: Expecting numeric in AY239 / R239C51: got 'NA'
## Warning: Expecting numeric in M240 / R240C13: got 'NA'
## Warning: Expecting numeric in N240 / R240C14: got 'NA'
## Warning: Expecting numeric in O240 / R240C15: got 'NA'
## Warning: Expecting numeric in R240 / R240C18: got 'NA'
## Warning: Expecting numeric in S240 / R240C19: got 'NA'
## Warning: Expecting numeric in T240 / R240C20: got 'NA'
## Warning: Expecting numeric in AY240 / R240C51: got 'NA'
## Warning: Expecting numeric in M241 / R241C13: got 'NA'
## Warning: Expecting numeric in N241 / R241C14: got 'NA'
## Warning: Expecting numeric in O241 / R241C15: got 'NA'
## Warning: Expecting numeric in R241 / R241C18: got 'NA'
## Warning: Expecting numeric in S241 / R241C19: got 'NA'
## Warning: Expecting numeric in T241 / R241C20: got 'NA'
## Warning: Expecting numeric in AY241 / R241C51: got 'NA'
## Warning: Expecting numeric in M242 / R242C13: got 'NA'
## Warning: Expecting numeric in N242 / R242C14: got 'NA'
## Warning: Expecting numeric in O242 / R242C15: got 'NA'
## Warning: Expecting numeric in R242 / R242C18: got 'NA'
## Warning: Expecting numeric in S242 / R242C19: got 'NA'
## Warning: Expecting numeric in T242 / R242C20: got 'NA'
## Warning: Expecting numeric in AY242 / R242C51: got 'NA'
## Warning: Expecting numeric in M243 / R243C13: got 'NA'
## Warning: Expecting numeric in N243 / R243C14: got 'NA'
## Warning: Expecting numeric in O243 / R243C15: got 'NA'
## Warning: Expecting numeric in R243 / R243C18: got 'NA'
## Warning: Expecting numeric in S243 / R243C19: got 'NA'
## Warning: Expecting numeric in T243 / R243C20: got 'NA'
## Warning: Expecting numeric in AY243 / R243C51: got 'NA'
## Warning: Expecting numeric in M244 / R244C13: got 'NA'
## Warning: Expecting numeric in N244 / R244C14: got 'NA'
## Warning: Expecting numeric in O244 / R244C15: got 'NA'
## Warning: Expecting numeric in R244 / R244C18: got 'NA'
## Warning: Expecting numeric in S244 / R244C19: got 'NA'
## Warning: Expecting numeric in T244 / R244C20: got 'NA'
## Warning: Expecting numeric in AV244 / R244C48: got 'NA'
## Warning: Expecting numeric in AY244 / R244C51: got 'NA'
## Warning: Expecting numeric in M245 / R245C13: got 'NA'
## Warning: Expecting numeric in N245 / R245C14: got 'NA'
## Warning: Expecting numeric in O245 / R245C15: got 'NA'
## Warning: Expecting numeric in R245 / R245C18: got 'NA'
## Warning: Expecting numeric in S245 / R245C19: got 'NA'
## Warning: Expecting numeric in T245 / R245C20: got 'NA'
## Warning: Expecting numeric in AY245 / R245C51: got 'NA'
## Warning: Expecting numeric in M246 / R246C13: got 'NA'
## Warning: Expecting numeric in N246 / R246C14: got 'NA'
## Warning: Expecting numeric in O246 / R246C15: got 'NA'
## Warning: Expecting numeric in R246 / R246C18: got 'NA'
## Warning: Expecting numeric in S246 / R246C19: got 'NA'
## Warning: Expecting numeric in T246 / R246C20: got 'NA'
## Warning: Expecting numeric in AY246 / R246C51: got 'NA'
## Warning: Expecting numeric in M247 / R247C13: got 'NA'
## Warning: Expecting numeric in N247 / R247C14: got 'NA'
## Warning: Expecting numeric in O247 / R247C15: got 'NA'
## Warning: Expecting numeric in R247 / R247C18: got 'NA'
## Warning: Expecting numeric in S247 / R247C19: got 'NA'
## Warning: Expecting numeric in T247 / R247C20: got 'NA'
## Warning: Expecting numeric in AY247 / R247C51: got 'NA'
## Warning: Expecting numeric in M248 / R248C13: got 'NA'
## Warning: Expecting numeric in N248 / R248C14: got 'NA'
## Warning: Expecting numeric in O248 / R248C15: got 'NA'
## Warning: Expecting numeric in R248 / R248C18: got 'NA'
## Warning: Expecting numeric in S248 / R248C19: got 'NA'
## Warning: Expecting numeric in T248 / R248C20: got 'NA'
## Warning: Expecting numeric in AY248 / R248C51: got 'NA'
## Warning: Expecting numeric in M249 / R249C13: got 'NA'
## Warning: Expecting numeric in N249 / R249C14: got 'NA'
## Warning: Expecting numeric in O249 / R249C15: got 'NA'
## Warning: Expecting numeric in R249 / R249C18: got 'NA'
## Warning: Expecting numeric in S249 / R249C19: got 'NA'
## Warning: Expecting numeric in T249 / R249C20: got 'NA'
## Warning: Expecting numeric in AY249 / R249C51: got 'NA'
## Warning: Expecting numeric in M250 / R250C13: got 'NA'
## Warning: Expecting numeric in N250 / R250C14: got 'NA'
## Warning: Expecting numeric in O250 / R250C15: got 'NA'
## Warning: Expecting numeric in R250 / R250C18: got 'NA'
## Warning: Expecting numeric in S250 / R250C19: got 'NA'
## Warning: Expecting numeric in T250 / R250C20: got 'NA'
## Warning: Expecting numeric in AY250 / R250C51: got 'NA'
## Warning: Expecting numeric in M251 / R251C13: got 'NA'
## Warning: Expecting numeric in N251 / R251C14: got 'NA'
## Warning: Expecting numeric in O251 / R251C15: got 'NA'
## Warning: Expecting numeric in R251 / R251C18: got 'NA'
## Warning: Expecting numeric in S251 / R251C19: got 'NA'
## Warning: Expecting numeric in T251 / R251C20: got 'NA'
## Warning: Expecting numeric in AY251 / R251C51: got 'NA'
## Warning: Expecting numeric in M252 / R252C13: got 'NA'
## Warning: Expecting numeric in N252 / R252C14: got 'NA'
## Warning: Expecting numeric in O252 / R252C15: got 'NA'
## Warning: Expecting numeric in R252 / R252C18: got 'NA'
## Warning: Expecting numeric in S252 / R252C19: got 'NA'
## Warning: Expecting numeric in T252 / R252C20: got 'NA'
## Warning: Expecting numeric in AY252 / R252C51: got 'NA'
## Warning: Expecting numeric in M253 / R253C13: got 'NA'
## Warning: Expecting numeric in N253 / R253C14: got 'NA'
## Warning: Expecting numeric in O253 / R253C15: got 'NA'
## Warning: Expecting numeric in R253 / R253C18: got 'NA'
## Warning: Expecting numeric in S253 / R253C19: got 'NA'
## Warning: Expecting numeric in T253 / R253C20: got 'NA'
## Warning: Expecting numeric in AY253 / R253C51: got 'NA'
## Warning: Expecting numeric in M254 / R254C13: got 'NA'
## Warning: Expecting numeric in N254 / R254C14: got 'NA'
## Warning: Expecting numeric in O254 / R254C15: got 'NA'
## Warning: Expecting numeric in R254 / R254C18: got 'NA'
## Warning: Expecting numeric in S254 / R254C19: got 'NA'
## Warning: Expecting numeric in T254 / R254C20: got 'NA'
## Warning: Expecting numeric in AY254 / R254C51: got 'NA'
## Warning: Expecting numeric in M255 / R255C13: got 'NA'
## Warning: Expecting numeric in N255 / R255C14: got 'NA'
## Warning: Expecting numeric in O255 / R255C15: got 'NA'
## Warning: Expecting numeric in R255 / R255C18: got 'NA'
## Warning: Expecting numeric in S255 / R255C19: got 'NA'
## Warning: Expecting numeric in T255 / R255C20: got 'NA'
## Warning: Expecting numeric in AY255 / R255C51: got 'NA'
## Warning: Expecting numeric in M256 / R256C13: got 'NA'
## Warning: Expecting numeric in N256 / R256C14: got 'NA'
## Warning: Expecting numeric in O256 / R256C15: got 'NA'
## Warning: Expecting numeric in R256 / R256C18: got 'NA'
## Warning: Expecting numeric in S256 / R256C19: got 'NA'
## Warning: Expecting numeric in T256 / R256C20: got 'NA'
## Warning: Expecting numeric in AY256 / R256C51: got 'NA'
## Warning: Expecting numeric in M257 / R257C13: got 'NA'
## Warning: Expecting numeric in N257 / R257C14: got 'NA'
## Warning: Expecting numeric in O257 / R257C15: got 'NA'
## Warning: Expecting numeric in R257 / R257C18: got 'NA'
## Warning: Expecting numeric in S257 / R257C19: got 'NA'
## Warning: Expecting numeric in T257 / R257C20: got 'NA'
## Warning: Expecting numeric in AY257 / R257C51: got 'NA'
## Warning: Expecting numeric in M258 / R258C13: got 'NA'
## Warning: Expecting numeric in N258 / R258C14: got 'NA'
## Warning: Expecting numeric in O258 / R258C15: got 'NA'
## Warning: Expecting numeric in R258 / R258C18: got 'NA'
## Warning: Expecting numeric in S258 / R258C19: got 'NA'
## Warning: Expecting numeric in T258 / R258C20: got 'NA'
## Warning: Expecting numeric in AY258 / R258C51: got 'NA'
## Warning: Expecting numeric in M259 / R259C13: got 'NA'
## Warning: Expecting numeric in N259 / R259C14: got 'NA'
## Warning: Expecting numeric in O259 / R259C15: got 'NA'
## Warning: Expecting numeric in R259 / R259C18: got 'NA'
## Warning: Expecting numeric in S259 / R259C19: got 'NA'
## Warning: Expecting numeric in T259 / R259C20: got 'NA'
## Warning: Expecting numeric in AY259 / R259C51: got 'NA'
## Warning: Expecting numeric in M260 / R260C13: got 'NA'
## Warning: Expecting numeric in N260 / R260C14: got 'NA'
## Warning: Expecting numeric in O260 / R260C15: got 'NA'
## Warning: Expecting numeric in R260 / R260C18: got 'NA'
## Warning: Expecting numeric in S260 / R260C19: got 'NA'
## Warning: Expecting numeric in T260 / R260C20: got 'NA'
## Warning: Expecting numeric in AY260 / R260C51: got 'NA'
## Warning: Expecting numeric in M261 / R261C13: got 'NA'
## Warning: Expecting numeric in N261 / R261C14: got 'NA'
## Warning: Expecting numeric in O261 / R261C15: got 'NA'
## Warning: Expecting numeric in R261 / R261C18: got 'NA'
## Warning: Expecting numeric in S261 / R261C19: got 'NA'
## Warning: Expecting numeric in T261 / R261C20: got 'NA'
## Warning: Expecting numeric in AY261 / R261C51: got 'NA'
## Warning: Expecting numeric in M262 / R262C13: got 'NA'
## Warning: Expecting numeric in N262 / R262C14: got 'NA'
## Warning: Expecting numeric in O262 / R262C15: got 'NA'
## Warning: Expecting numeric in R262 / R262C18: got 'NA'
## Warning: Expecting numeric in S262 / R262C19: got 'NA'
## Warning: Expecting numeric in T262 / R262C20: got 'NA'
## Warning: Expecting numeric in AY262 / R262C51: got 'NA'
## Warning: Expecting numeric in M263 / R263C13: got 'NA'
## Warning: Expecting numeric in N263 / R263C14: got 'NA'
## Warning: Expecting numeric in O263 / R263C15: got 'NA'
## Warning: Expecting numeric in R263 / R263C18: got 'NA'
## Warning: Expecting numeric in S263 / R263C19: got 'NA'
## Warning: Expecting numeric in T263 / R263C20: got 'NA'
## Warning: Expecting numeric in AY263 / R263C51: got 'NA'
## Warning: Expecting numeric in M264 / R264C13: got 'NA'
## Warning: Expecting numeric in N264 / R264C14: got 'NA'
## Warning: Expecting numeric in O264 / R264C15: got 'NA'
## Warning: Expecting numeric in R264 / R264C18: got 'NA'
## Warning: Expecting numeric in S264 / R264C19: got 'NA'
## Warning: Expecting numeric in T264 / R264C20: got 'NA'
## Warning: Expecting numeric in AY264 / R264C51: got 'NA'
## Warning: Expecting numeric in M265 / R265C13: got 'NA'
## Warning: Expecting numeric in N265 / R265C14: got 'NA'
## Warning: Expecting numeric in O265 / R265C15: got 'NA'
## Warning: Expecting numeric in R265 / R265C18: got 'NA'
## Warning: Expecting numeric in S265 / R265C19: got 'NA'
## Warning: Expecting numeric in T265 / R265C20: got 'NA'
## Warning: Expecting numeric in AY265 / R265C51: got 'NA'
## Warning: Expecting numeric in M266 / R266C13: got 'NA'
## Warning: Expecting numeric in N266 / R266C14: got 'NA'
## Warning: Expecting numeric in O266 / R266C15: got 'NA'
## Warning: Expecting numeric in R266 / R266C18: got 'NA'
## Warning: Expecting numeric in S266 / R266C19: got 'NA'
## Warning: Expecting numeric in T266 / R266C20: got 'NA'
## Warning: Expecting numeric in AY266 / R266C51: got 'NA'
## Warning: Expecting numeric in M267 / R267C13: got 'NA'
## Warning: Expecting numeric in N267 / R267C14: got 'NA'
## Warning: Expecting numeric in O267 / R267C15: got 'NA'
## Warning: Expecting numeric in R267 / R267C18: got 'NA'
## Warning: Expecting numeric in S267 / R267C19: got 'NA'
## Warning: Expecting numeric in T267 / R267C20: got 'NA'
## Warning: Expecting numeric in AV267 / R267C48: got 'NA'
## Warning: Expecting numeric in AY267 / R267C51: got 'NA'
## Warning: Expecting numeric in M268 / R268C13: got 'NA'
## Warning: Expecting numeric in N268 / R268C14: got 'NA'
## Warning: Expecting numeric in O268 / R268C15: got 'NA'
## Warning: Expecting numeric in R268 / R268C18: got 'NA'
## Warning: Expecting numeric in S268 / R268C19: got 'NA'
## Warning: Expecting numeric in T268 / R268C20: got 'NA'
## Warning: Expecting numeric in AY268 / R268C51: got 'NA'
## Warning: Expecting numeric in M269 / R269C13: got 'NA'
## Warning: Expecting numeric in N269 / R269C14: got 'NA'
## Warning: Expecting numeric in O269 / R269C15: got 'NA'
## Warning: Expecting numeric in R269 / R269C18: got 'NA'
## Warning: Expecting numeric in S269 / R269C19: got 'NA'
## Warning: Expecting numeric in T269 / R269C20: got 'NA'
## Warning: Expecting numeric in AY269 / R269C51: got 'NA'
## Warning: Expecting numeric in M270 / R270C13: got 'NA'
## Warning: Expecting numeric in N270 / R270C14: got 'NA'
## Warning: Expecting numeric in O270 / R270C15: got 'NA'
## Warning: Expecting numeric in R270 / R270C18: got 'NA'
## Warning: Expecting numeric in S270 / R270C19: got 'NA'
## Warning: Expecting numeric in T270 / R270C20: got 'NA'
## Warning: Expecting numeric in M271 / R271C13: got 'NA'
## Warning: Expecting numeric in N271 / R271C14: got 'NA'
## Warning: Expecting numeric in O271 / R271C15: got 'NA'
## Warning: Expecting numeric in R271 / R271C18: got 'NA'
## Warning: Expecting numeric in S271 / R271C19: got 'NA'
## Warning: Expecting numeric in T271 / R271C20: got 'NA'
## Warning: Expecting numeric in AY271 / R271C51: got 'NA'
## Warning: Expecting numeric in M272 / R272C13: got 'NA'
## Warning: Expecting numeric in N272 / R272C14: got 'NA'
## Warning: Expecting numeric in O272 / R272C15: got 'NA'
## Warning: Expecting numeric in R272 / R272C18: got 'NA'
## Warning: Expecting numeric in S272 / R272C19: got 'NA'
## Warning: Expecting numeric in T272 / R272C20: got 'NA'
## Warning: Expecting numeric in AY272 / R272C51: got 'NA'
## Warning: Expecting numeric in M273 / R273C13: got 'NA'
## Warning: Expecting numeric in N273 / R273C14: got 'NA'
## Warning: Expecting numeric in O273 / R273C15: got 'NA'
## Warning: Expecting numeric in R273 / R273C18: got 'NA'
## Warning: Expecting numeric in S273 / R273C19: got 'NA'
## Warning: Expecting numeric in T273 / R273C20: got 'NA'
## Warning: Expecting numeric in AY273 / R273C51: got 'NA'
## Warning: Expecting numeric in M274 / R274C13: got 'NA'
## Warning: Expecting numeric in N274 / R274C14: got 'NA'
## Warning: Expecting numeric in O274 / R274C15: got 'NA'
## Warning: Expecting numeric in R274 / R274C18: got 'NA'
## Warning: Expecting numeric in S274 / R274C19: got 'NA'
## Warning: Expecting numeric in T274 / R274C20: got 'NA'
## Warning: Expecting numeric in M275 / R275C13: got 'NA'
## Warning: Expecting numeric in N275 / R275C14: got 'NA'
## Warning: Expecting numeric in O275 / R275C15: got 'NA'
## Warning: Expecting numeric in R275 / R275C18: got 'NA'
## Warning: Expecting numeric in S275 / R275C19: got 'NA'
## Warning: Expecting numeric in T275 / R275C20: got 'NA'
## Warning: Expecting numeric in AY275 / R275C51: got 'NA'
## Warning: Expecting numeric in M276 / R276C13: got 'NA'
## Warning: Expecting numeric in N276 / R276C14: got 'NA'
## Warning: Expecting numeric in O276 / R276C15: got 'NA'
## Warning: Expecting numeric in R276 / R276C18: got 'NA'
## Warning: Expecting numeric in S276 / R276C19: got 'NA'
## Warning: Expecting numeric in T276 / R276C20: got 'NA'
## Warning: Expecting numeric in AY276 / R276C51: got 'NA'
## Warning: Expecting numeric in M277 / R277C13: got 'NA'
## Warning: Expecting numeric in N277 / R277C14: got 'NA'
## Warning: Expecting numeric in O277 / R277C15: got 'NA'
## Warning: Expecting numeric in R277 / R277C18: got 'NA'
## Warning: Expecting numeric in S277 / R277C19: got 'NA'
## Warning: Expecting numeric in T277 / R277C20: got 'NA'
## Warning: Expecting numeric in AY277 / R277C51: got 'NA'
## Warning: Expecting numeric in M278 / R278C13: got 'NA'
## Warning: Expecting numeric in N278 / R278C14: got 'NA'
## Warning: Expecting numeric in O278 / R278C15: got 'NA'
## Warning: Expecting numeric in R278 / R278C18: got 'NA'
## Warning: Expecting numeric in S278 / R278C19: got 'NA'
## Warning: Expecting numeric in T278 / R278C20: got 'NA'
## Warning: Expecting numeric in AY278 / R278C51: got 'NA'
## Warning: Expecting numeric in M279 / R279C13: got 'NA'
## Warning: Expecting numeric in N279 / R279C14: got 'NA'
## Warning: Expecting numeric in O279 / R279C15: got 'NA'
## Warning: Expecting numeric in R279 / R279C18: got 'NA'
## Warning: Expecting numeric in S279 / R279C19: got 'NA'
## Warning: Expecting numeric in T279 / R279C20: got 'NA'
## Warning: Expecting numeric in AY279 / R279C51: got 'NA'
## Warning: Expecting numeric in M280 / R280C13: got 'NA'
## Warning: Expecting numeric in N280 / R280C14: got 'NA'
## Warning: Expecting numeric in O280 / R280C15: got 'NA'
## Warning: Expecting numeric in R280 / R280C18: got 'NA'
## Warning: Expecting numeric in S280 / R280C19: got 'NA'
## Warning: Expecting numeric in T280 / R280C20: got 'NA'
## Warning: Expecting numeric in X280 / R280C24: got 'NA'
## Warning: Expecting numeric in M281 / R281C13: got 'NA'
## Warning: Expecting numeric in N281 / R281C14: got 'NA'
## Warning: Expecting numeric in O281 / R281C15: got 'NA'
## Warning: Expecting numeric in R281 / R281C18: got 'NA'
## Warning: Expecting numeric in S281 / R281C19: got 'NA'
## Warning: Expecting numeric in T281 / R281C20: got 'NA'
## Warning: Expecting numeric in M282 / R282C13: got 'NA'
## Warning: Expecting numeric in N282 / R282C14: got 'NA'
## Warning: Expecting numeric in O282 / R282C15: got 'NA'
## Warning: Expecting numeric in R282 / R282C18: got 'NA'
## Warning: Expecting numeric in S282 / R282C19: got 'NA'
## Warning: Expecting numeric in T282 / R282C20: got 'NA'
## Warning: Expecting numeric in M283 / R283C13: got 'NA'
## Warning: Expecting numeric in N283 / R283C14: got 'NA'
## Warning: Expecting numeric in O283 / R283C15: got 'NA'
## Warning: Expecting numeric in R283 / R283C18: got 'NA'
## Warning: Expecting numeric in S283 / R283C19: got 'NA'
## Warning: Expecting numeric in T283 / R283C20: got 'NA'
## Warning: Expecting numeric in M284 / R284C13: got 'NA'
## Warning: Expecting numeric in N284 / R284C14: got 'NA'
## Warning: Expecting numeric in O284 / R284C15: got 'NA'
## Warning: Expecting numeric in R284 / R284C18: got 'NA'
## Warning: Expecting numeric in S284 / R284C19: got 'NA'
## Warning: Expecting numeric in T284 / R284C20: got 'NA'
## Warning: Expecting numeric in M285 / R285C13: got 'NA'
## Warning: Expecting numeric in N285 / R285C14: got 'NA'
## Warning: Expecting numeric in O285 / R285C15: got 'NA'
## Warning: Expecting numeric in R285 / R285C18: got 'NA'
## Warning: Expecting numeric in S285 / R285C19: got 'NA'
## Warning: Expecting numeric in T285 / R285C20: got 'NA'
## Warning: Expecting numeric in M286 / R286C13: got 'NA'
## Warning: Expecting numeric in N286 / R286C14: got 'NA'
## Warning: Expecting numeric in O286 / R286C15: got 'NA'
## Warning: Expecting numeric in R286 / R286C18: got 'NA'
## Warning: Expecting numeric in S286 / R286C19: got 'NA'
## Warning: Expecting numeric in T286 / R286C20: got 'NA'
## Warning: Expecting numeric in M287 / R287C13: got 'NA'
## Warning: Expecting numeric in N287 / R287C14: got 'NA'
## Warning: Expecting numeric in O287 / R287C15: got 'NA'
## Warning: Expecting numeric in R287 / R287C18: got 'NA'
## Warning: Expecting numeric in S287 / R287C19: got 'NA'
## Warning: Expecting numeric in T287 / R287C20: got 'NA'
## Warning: Expecting numeric in M288 / R288C13: got 'NA'
## Warning: Expecting numeric in N288 / R288C14: got 'NA'
## Warning: Expecting numeric in O288 / R288C15: got 'NA'
## Warning: Expecting numeric in R288 / R288C18: got 'NA'
## Warning: Expecting numeric in S288 / R288C19: got 'NA'
## Warning: Expecting numeric in T288 / R288C20: got 'NA'
## Warning: Expecting numeric in M289 / R289C13: got 'NA'
## Warning: Expecting numeric in N289 / R289C14: got 'NA'
## Warning: Expecting numeric in O289 / R289C15: got 'NA'
## Warning: Expecting numeric in R289 / R289C18: got 'NA'
## Warning: Expecting numeric in S289 / R289C19: got 'NA'
## Warning: Expecting numeric in T289 / R289C20: got 'NA'
## Warning: Expecting numeric in M290 / R290C13: got 'NA'
## Warning: Expecting numeric in N290 / R290C14: got 'NA'
## Warning: Expecting numeric in O290 / R290C15: got 'NA'
## Warning: Expecting numeric in R290 / R290C18: got 'NA'
## Warning: Expecting numeric in S290 / R290C19: got 'NA'
## Warning: Expecting numeric in T290 / R290C20: got 'NA'
## Warning: Expecting numeric in M291 / R291C13: got 'NA'
## Warning: Expecting numeric in N291 / R291C14: got 'NA'
## Warning: Expecting numeric in O291 / R291C15: got 'NA'
## Warning: Expecting numeric in R291 / R291C18: got 'NA'
## Warning: Expecting numeric in S291 / R291C19: got 'NA'
## Warning: Expecting numeric in T291 / R291C20: got 'NA'
## Warning: Expecting numeric in M292 / R292C13: got 'NA'
## Warning: Expecting numeric in N292 / R292C14: got 'NA'
## Warning: Expecting numeric in O292 / R292C15: got 'NA'
## Warning: Expecting numeric in R292 / R292C18: got 'NA'
## Warning: Expecting numeric in S292 / R292C19: got 'NA'
## Warning: Expecting numeric in T292 / R292C20: got 'NA'
## Warning: Expecting numeric in M293 / R293C13: got 'NA'
## Warning: Expecting numeric in N293 / R293C14: got 'NA'
## Warning: Expecting numeric in O293 / R293C15: got 'NA'
## Warning: Expecting numeric in R293 / R293C18: got 'NA'
## Warning: Expecting numeric in S293 / R293C19: got 'NA'
## Warning: Expecting numeric in T293 / R293C20: got 'NA'
## Warning: Expecting numeric in M294 / R294C13: got 'NA'
## Warning: Expecting numeric in N294 / R294C14: got 'NA'
## Warning: Expecting numeric in O294 / R294C15: got 'NA'
## Warning: Expecting numeric in R294 / R294C18: got 'NA'
## Warning: Expecting numeric in S294 / R294C19: got 'NA'
## Warning: Expecting numeric in T294 / R294C20: got 'NA'
## Warning: Expecting numeric in M295 / R295C13: got 'NA'
## Warning: Expecting numeric in N295 / R295C14: got 'NA'
## Warning: Expecting numeric in O295 / R295C15: got 'NA'
## Warning: Expecting numeric in R295 / R295C18: got 'NA'
## Warning: Expecting numeric in S295 / R295C19: got 'NA'
## Warning: Expecting numeric in T295 / R295C20: got 'NA'
## Warning: Expecting numeric in M296 / R296C13: got 'NA'
## Warning: Expecting numeric in N296 / R296C14: got 'NA'
## Warning: Expecting numeric in O296 / R296C15: got 'NA'
## Warning: Expecting numeric in R296 / R296C18: got 'NA'
## Warning: Expecting numeric in S296 / R296C19: got 'NA'
## Warning: Expecting numeric in T296 / R296C20: got 'NA'
## Warning: Expecting numeric in X296 / R296C24: got 'NA'
## Warning: Expecting numeric in M297 / R297C13: got 'NA'
## Warning: Expecting numeric in N297 / R297C14: got 'NA'
## Warning: Expecting numeric in O297 / R297C15: got 'NA'
## Warning: Expecting numeric in R297 / R297C18: got 'NA'
## Warning: Expecting numeric in S297 / R297C19: got 'NA'
## Warning: Expecting numeric in T297 / R297C20: got 'NA'
## Warning: Expecting numeric in X297 / R297C24: got 'NA'
## Warning: Expecting numeric in M298 / R298C13: got 'NA'
## Warning: Expecting numeric in N298 / R298C14: got 'NA'
## Warning: Expecting numeric in O298 / R298C15: got 'NA'
## Warning: Expecting numeric in R298 / R298C18: got 'NA'
## Warning: Expecting numeric in S298 / R298C19: got 'NA'
## Warning: Expecting numeric in T298 / R298C20: got 'NA'
## Warning: Expecting numeric in X298 / R298C24: got 'NA'
## Warning: Expecting numeric in M299 / R299C13: got 'NA'
## Warning: Expecting numeric in N299 / R299C14: got 'NA'
## Warning: Expecting numeric in O299 / R299C15: got 'NA'
## Warning: Expecting numeric in R299 / R299C18: got 'NA'
## Warning: Expecting numeric in S299 / R299C19: got 'NA'
## Warning: Expecting numeric in T299 / R299C20: got 'NA'
## Warning: Expecting numeric in X299 / R299C24: got 'NA'
## Warning: Expecting numeric in M300 / R300C13: got 'NA'
## Warning: Expecting numeric in N300 / R300C14: got 'NA'
## Warning: Expecting numeric in O300 / R300C15: got 'NA'
## Warning: Expecting numeric in R300 / R300C18: got 'NA'
## Warning: Expecting numeric in S300 / R300C19: got 'NA'
## Warning: Expecting numeric in T300 / R300C20: got 'NA'
## Warning: Expecting numeric in X300 / R300C24: got 'NA'
## Warning: Expecting numeric in M301 / R301C13: got 'NA'
## Warning: Expecting numeric in N301 / R301C14: got 'NA'
## Warning: Expecting numeric in O301 / R301C15: got 'NA'
## Warning: Expecting numeric in R301 / R301C18: got 'NA'
## Warning: Expecting numeric in S301 / R301C19: got 'NA'
## Warning: Expecting numeric in T301 / R301C20: got 'NA'
## Warning: Expecting numeric in X301 / R301C24: got 'NA'
## Warning: Expecting numeric in M302 / R302C13: got 'NA'
## Warning: Expecting numeric in N302 / R302C14: got 'NA'
## Warning: Expecting numeric in O302 / R302C15: got 'NA'
## Warning: Expecting numeric in R302 / R302C18: got 'NA'
## Warning: Expecting numeric in S302 / R302C19: got 'NA'
## Warning: Expecting numeric in T302 / R302C20: got 'NA'
## Warning: Expecting numeric in X302 / R302C24: got 'NA'
## Warning: Expecting numeric in M303 / R303C13: got 'NA'
## Warning: Expecting numeric in N303 / R303C14: got 'NA'
## Warning: Expecting numeric in O303 / R303C15: got 'NA'
## Warning: Expecting numeric in R303 / R303C18: got 'NA'
## Warning: Expecting numeric in S303 / R303C19: got 'NA'
## Warning: Expecting numeric in T303 / R303C20: got 'NA'
## Warning: Expecting numeric in X303 / R303C24: got 'NA'
## Warning: Expecting numeric in M304 / R304C13: got 'NA'
## Warning: Expecting numeric in N304 / R304C14: got 'NA'
## Warning: Expecting numeric in O304 / R304C15: got 'NA'
## Warning: Expecting numeric in R304 / R304C18: got 'NA'
## Warning: Expecting numeric in S304 / R304C19: got 'NA'
## Warning: Expecting numeric in T304 / R304C20: got 'NA'
## Warning: Expecting numeric in M305 / R305C13: got 'NA'
## Warning: Expecting numeric in N305 / R305C14: got 'NA'
## Warning: Expecting numeric in O305 / R305C15: got 'NA'
## Warning: Expecting numeric in R305 / R305C18: got 'NA'
## Warning: Expecting numeric in S305 / R305C19: got 'NA'
## Warning: Expecting numeric in T305 / R305C20: got 'NA'
## Warning: Expecting numeric in M306 / R306C13: got 'NA'
## Warning: Expecting numeric in N306 / R306C14: got 'NA'
## Warning: Expecting numeric in O306 / R306C15: got 'NA'
## Warning: Expecting numeric in R306 / R306C18: got 'NA'
## Warning: Expecting numeric in S306 / R306C19: got 'NA'
## Warning: Expecting numeric in T306 / R306C20: got 'NA'
## Warning: Expecting numeric in M307 / R307C13: got 'NA'
## Warning: Expecting numeric in N307 / R307C14: got 'NA'
## Warning: Expecting numeric in O307 / R307C15: got 'NA'
## Warning: Expecting numeric in R307 / R307C18: got 'NA'
## Warning: Expecting numeric in S307 / R307C19: got 'NA'
## Warning: Expecting numeric in T307 / R307C20: got 'NA'
## Warning: Expecting numeric in M308 / R308C13: got 'NA'
## Warning: Expecting numeric in N308 / R308C14: got 'NA'
## Warning: Expecting numeric in O308 / R308C15: got 'NA'
## Warning: Expecting numeric in R308 / R308C18: got 'NA'
## Warning: Expecting numeric in S308 / R308C19: got 'NA'
## Warning: Expecting numeric in T308 / R308C20: got 'NA'
## Warning: Expecting numeric in M309 / R309C13: got 'NA'
## Warning: Expecting numeric in N309 / R309C14: got 'NA'
## Warning: Expecting numeric in O309 / R309C15: got 'NA'
## Warning: Expecting numeric in R309 / R309C18: got 'NA'
## Warning: Expecting numeric in S309 / R309C19: got 'NA'
## Warning: Expecting numeric in T309 / R309C20: got 'NA'
## Warning: Expecting numeric in M310 / R310C13: got 'NA'
## Warning: Expecting numeric in N310 / R310C14: got 'NA'
## Warning: Expecting numeric in O310 / R310C15: got 'NA'
## Warning: Expecting numeric in R310 / R310C18: got 'NA'
## Warning: Expecting numeric in S310 / R310C19: got 'NA'
## Warning: Expecting numeric in T310 / R310C20: got 'NA'
## Warning: Expecting numeric in M311 / R311C13: got 'NA'
## Warning: Expecting numeric in N311 / R311C14: got 'NA'
## Warning: Expecting numeric in O311 / R311C15: got 'NA'
## Warning: Expecting numeric in R311 / R311C18: got 'NA'
## Warning: Expecting numeric in S311 / R311C19: got 'NA'
## Warning: Expecting numeric in T311 / R311C20: got 'NA'
## Warning: Expecting numeric in M312 / R312C13: got 'NA'
## Warning: Expecting numeric in N312 / R312C14: got 'NA'
## Warning: Expecting numeric in O312 / R312C15: got 'NA'
## Warning: Expecting numeric in R312 / R312C18: got 'NA'
## Warning: Expecting numeric in S312 / R312C19: got 'NA'
## Warning: Expecting numeric in T312 / R312C20: got 'NA'
## Warning: Expecting numeric in M313 / R313C13: got 'NA'
## Warning: Expecting numeric in N313 / R313C14: got 'NA'
## Warning: Expecting numeric in O313 / R313C15: got 'NA'
## Warning: Expecting numeric in R313 / R313C18: got 'NA'
## Warning: Expecting numeric in S313 / R313C19: got 'NA'
## Warning: Expecting numeric in T313 / R313C20: got 'NA'
## Warning: Expecting numeric in M314 / R314C13: got 'NA'
## Warning: Expecting numeric in N314 / R314C14: got 'NA'
## Warning: Expecting numeric in O314 / R314C15: got 'NA'
## Warning: Expecting numeric in R314 / R314C18: got 'NA'
## Warning: Expecting numeric in S314 / R314C19: got 'NA'
## Warning: Expecting numeric in T314 / R314C20: got 'NA'
## Warning: Expecting numeric in M315 / R315C13: got 'NA'
## Warning: Expecting numeric in N315 / R315C14: got 'NA'
## Warning: Expecting numeric in O315 / R315C15: got 'NA'
## Warning: Expecting numeric in R315 / R315C18: got 'NA'
## Warning: Expecting numeric in S315 / R315C19: got 'NA'
## Warning: Expecting numeric in T315 / R315C20: got 'NA'
## Warning: Expecting numeric in M316 / R316C13: got 'NA'
## Warning: Expecting numeric in N316 / R316C14: got 'NA'
## Warning: Expecting numeric in O316 / R316C15: got 'NA'
## Warning: Expecting numeric in R316 / R316C18: got 'NA'
## Warning: Expecting numeric in S316 / R316C19: got 'NA'
## Warning: Expecting numeric in T316 / R316C20: got 'NA'
## Warning: Expecting numeric in M317 / R317C13: got 'NA'
## Warning: Expecting numeric in N317 / R317C14: got 'NA'
## Warning: Expecting numeric in O317 / R317C15: got 'NA'
## Warning: Expecting numeric in R317 / R317C18: got 'NA'
## Warning: Expecting numeric in S317 / R317C19: got 'NA'
## Warning: Expecting numeric in T317 / R317C20: got 'NA'
## Warning: Expecting numeric in M318 / R318C13: got 'NA'
## Warning: Expecting numeric in N318 / R318C14: got 'NA'
## Warning: Expecting numeric in O318 / R318C15: got 'NA'
## Warning: Expecting numeric in R318 / R318C18: got 'NA'
## Warning: Expecting numeric in S318 / R318C19: got 'NA'
## Warning: Expecting numeric in T318 / R318C20: got 'NA'
## Warning: Expecting numeric in M319 / R319C13: got 'NA'
## Warning: Expecting numeric in N319 / R319C14: got 'NA'
## Warning: Expecting numeric in O319 / R319C15: got 'NA'
## Warning: Expecting numeric in R319 / R319C18: got 'NA'
## Warning: Expecting numeric in S319 / R319C19: got 'NA'
## Warning: Expecting numeric in T319 / R319C20: got 'NA'
## Warning: Expecting numeric in M320 / R320C13: got 'NA'
## Warning: Expecting numeric in N320 / R320C14: got 'NA'
## Warning: Expecting numeric in O320 / R320C15: got 'NA'
## Warning: Expecting numeric in R320 / R320C18: got 'NA'
## Warning: Expecting numeric in S320 / R320C19: got 'NA'
## Warning: Expecting numeric in T320 / R320C20: got 'NA'
## Warning: Expecting numeric in M321 / R321C13: got 'NA'
## Warning: Expecting numeric in N321 / R321C14: got 'NA'
## Warning: Expecting numeric in O321 / R321C15: got 'NA'
## Warning: Expecting numeric in R321 / R321C18: got 'NA'
## Warning: Expecting numeric in S321 / R321C19: got 'NA'
## Warning: Expecting numeric in T321 / R321C20: got 'NA'
## Warning: Expecting numeric in M322 / R322C13: got 'NA'
## Warning: Expecting numeric in N322 / R322C14: got 'NA'
## Warning: Expecting numeric in O322 / R322C15: got 'NA'
## Warning: Expecting numeric in R322 / R322C18: got 'NA'
## Warning: Expecting numeric in S322 / R322C19: got 'NA'
## Warning: Expecting numeric in T322 / R322C20: got 'NA'
## Warning: Expecting numeric in M323 / R323C13: got 'NA'
## Warning: Expecting numeric in N323 / R323C14: got 'NA'
## Warning: Expecting numeric in O323 / R323C15: got 'NA'
## Warning: Expecting numeric in R323 / R323C18: got 'NA'
## Warning: Expecting numeric in S323 / R323C19: got 'NA'
## Warning: Expecting numeric in T323 / R323C20: got 'NA'
## Warning: Expecting numeric in M324 / R324C13: got 'NA'
## Warning: Expecting numeric in N324 / R324C14: got 'NA'
## Warning: Expecting numeric in O324 / R324C15: got 'NA'
## Warning: Expecting numeric in R324 / R324C18: got 'NA'
## Warning: Expecting numeric in S324 / R324C19: got 'NA'
## Warning: Expecting numeric in T324 / R324C20: got 'NA'
## Warning: Expecting numeric in M325 / R325C13: got 'NA'
## Warning: Expecting numeric in N325 / R325C14: got 'NA'
## Warning: Expecting numeric in O325 / R325C15: got 'NA'
## Warning: Expecting numeric in R325 / R325C18: got 'NA'
## Warning: Expecting numeric in S325 / R325C19: got 'NA'
## Warning: Expecting numeric in T325 / R325C20: got 'NA'
## Warning: Expecting numeric in M326 / R326C13: got 'NA'
## Warning: Expecting numeric in N326 / R326C14: got 'NA'
## Warning: Expecting numeric in O326 / R326C15: got 'NA'
## Warning: Expecting numeric in R326 / R326C18: got 'NA'
## Warning: Expecting numeric in S326 / R326C19: got 'NA'
## Warning: Expecting numeric in T326 / R326C20: got 'NA'
## Warning: Expecting numeric in M327 / R327C13: got 'NA'
## Warning: Expecting numeric in N327 / R327C14: got 'NA'
## Warning: Expecting numeric in O327 / R327C15: got 'NA'
## Warning: Expecting numeric in R327 / R327C18: got 'NA'
## Warning: Expecting numeric in S327 / R327C19: got 'NA'
## Warning: Expecting numeric in T327 / R327C20: got 'NA'
## Warning: Expecting numeric in M328 / R328C13: got 'NA'
## Warning: Expecting numeric in N328 / R328C14: got 'NA'
## Warning: Expecting numeric in O328 / R328C15: got 'NA'
## Warning: Expecting numeric in R328 / R328C18: got 'NA'
## Warning: Expecting numeric in S328 / R328C19: got 'NA'
## Warning: Expecting numeric in T328 / R328C20: got 'NA'
## Warning: Expecting numeric in M329 / R329C13: got 'NA'
## Warning: Expecting numeric in N329 / R329C14: got 'NA'
## Warning: Expecting numeric in O329 / R329C15: got 'NA'
## Warning: Expecting numeric in R329 / R329C18: got 'NA'
## Warning: Expecting numeric in S329 / R329C19: got 'NA'
## Warning: Expecting numeric in T329 / R329C20: got 'NA'
## Warning: Expecting numeric in M330 / R330C13: got 'NA'
## Warning: Expecting numeric in N330 / R330C14: got 'NA'
## Warning: Expecting numeric in O330 / R330C15: got 'NA'
## Warning: Expecting numeric in R330 / R330C18: got 'NA'
## Warning: Expecting numeric in S330 / R330C19: got 'NA'
## Warning: Expecting numeric in T330 / R330C20: got 'NA'
## Warning: Expecting numeric in M331 / R331C13: got 'NA'
## Warning: Expecting numeric in N331 / R331C14: got 'NA'
## Warning: Expecting numeric in O331 / R331C15: got 'NA'
## Warning: Expecting numeric in R331 / R331C18: got 'NA'
## Warning: Expecting numeric in S331 / R331C19: got 'NA'
## Warning: Expecting numeric in T331 / R331C20: got 'NA'
## Warning: Expecting numeric in M332 / R332C13: got 'NA'
## Warning: Expecting numeric in N332 / R332C14: got 'NA'
## Warning: Expecting numeric in O332 / R332C15: got 'NA'
## Warning: Expecting numeric in R332 / R332C18: got 'NA'
## Warning: Expecting numeric in S332 / R332C19: got 'NA'
## Warning: Expecting numeric in T332 / R332C20: got 'NA'
## Warning: Expecting numeric in M333 / R333C13: got 'NA'
## Warning: Expecting numeric in N333 / R333C14: got 'NA'
## Warning: Expecting numeric in O333 / R333C15: got 'NA'
## Warning: Expecting numeric in R333 / R333C18: got 'NA'
## Warning: Expecting numeric in S333 / R333C19: got 'NA'
## Warning: Expecting numeric in T333 / R333C20: got 'NA'
## Warning: Expecting numeric in M334 / R334C13: got 'NA'
## Warning: Expecting numeric in N334 / R334C14: got 'NA'
## Warning: Expecting numeric in O334 / R334C15: got 'NA'
## Warning: Expecting numeric in R334 / R334C18: got 'NA'
## Warning: Expecting numeric in S334 / R334C19: got 'NA'
## Warning: Expecting numeric in T334 / R334C20: got 'NA'
## Warning: Expecting numeric in M335 / R335C13: got 'NA'
## Warning: Expecting numeric in N335 / R335C14: got 'NA'
## Warning: Expecting numeric in O335 / R335C15: got 'NA'
## Warning: Expecting numeric in R335 / R335C18: got 'NA'
## Warning: Expecting numeric in S335 / R335C19: got 'NA'
## Warning: Expecting numeric in T335 / R335C20: got 'NA'
## Warning: Expecting numeric in M336 / R336C13: got 'NA'
## Warning: Expecting numeric in N336 / R336C14: got 'NA'
## Warning: Expecting numeric in O336 / R336C15: got 'NA'
## Warning: Expecting numeric in R336 / R336C18: got 'NA'
## Warning: Expecting numeric in S336 / R336C19: got 'NA'
## Warning: Expecting numeric in T336 / R336C20: got 'NA'
## Warning: Expecting numeric in M337 / R337C13: got 'NA'
## Warning: Expecting numeric in N337 / R337C14: got 'NA'
## Warning: Expecting numeric in O337 / R337C15: got 'NA'
## Warning: Expecting numeric in R337 / R337C18: got 'NA'
## Warning: Expecting numeric in S337 / R337C19: got 'NA'
## Warning: Expecting numeric in T337 / R337C20: got 'NA'
## Warning: Expecting numeric in M338 / R338C13: got 'NA'
## Warning: Expecting numeric in N338 / R338C14: got 'NA'
## Warning: Expecting numeric in O338 / R338C15: got 'NA'
## Warning: Expecting numeric in R338 / R338C18: got 'NA'
## Warning: Expecting numeric in S338 / R338C19: got 'NA'
## Warning: Expecting numeric in T338 / R338C20: got 'NA'
## Warning: Expecting numeric in M339 / R339C13: got 'NA'
## Warning: Expecting numeric in N339 / R339C14: got 'NA'
## Warning: Expecting numeric in O339 / R339C15: got 'NA'
## Warning: Expecting numeric in R339 / R339C18: got 'NA'
## Warning: Expecting numeric in S339 / R339C19: got 'NA'
## Warning: Expecting numeric in T339 / R339C20: got 'NA'
## Warning: Expecting numeric in M340 / R340C13: got 'NA'
## Warning: Expecting numeric in N340 / R340C14: got 'NA'
## Warning: Expecting numeric in O340 / R340C15: got 'NA'
## Warning: Expecting numeric in R340 / R340C18: got 'NA'
## Warning: Expecting numeric in S340 / R340C19: got 'NA'
## Warning: Expecting numeric in T340 / R340C20: got 'NA'
## Warning: Expecting numeric in M341 / R341C13: got 'NA'
## Warning: Expecting numeric in N341 / R341C14: got 'NA'
## Warning: Expecting numeric in O341 / R341C15: got 'NA'
## Warning: Expecting numeric in R341 / R341C18: got 'NA'
## Warning: Expecting numeric in S341 / R341C19: got 'NA'
## Warning: Expecting numeric in T341 / R341C20: got 'NA'
## Warning: Expecting numeric in M342 / R342C13: got 'NA'
## Warning: Expecting numeric in N342 / R342C14: got 'NA'
## Warning: Expecting numeric in O342 / R342C15: got 'NA'
## Warning: Expecting numeric in R342 / R342C18: got 'NA'
## Warning: Expecting numeric in S342 / R342C19: got 'NA'
## Warning: Expecting numeric in T342 / R342C20: got 'NA'
## Warning: Expecting numeric in M343 / R343C13: got 'NA'
## Warning: Expecting numeric in N343 / R343C14: got 'NA'
## Warning: Expecting numeric in O343 / R343C15: got 'NA'
## Warning: Expecting numeric in R343 / R343C18: got 'NA'
## Warning: Expecting numeric in S343 / R343C19: got 'NA'
## Warning: Expecting numeric in T343 / R343C20: got 'NA'
## Warning: Expecting numeric in X343 / R343C24: got 'NA'
## Warning: Expecting numeric in M344 / R344C13: got 'NA'
## Warning: Expecting numeric in N344 / R344C14: got 'NA'
## Warning: Expecting numeric in O344 / R344C15: got 'NA'
## Warning: Expecting numeric in R344 / R344C18: got 'NA'
## Warning: Expecting numeric in S344 / R344C19: got 'NA'
## Warning: Expecting numeric in T344 / R344C20: got 'NA'
## Warning: Expecting numeric in X344 / R344C24: got 'NA'
## Warning: Expecting numeric in M345 / R345C13: got 'NA'
## Warning: Expecting numeric in N345 / R345C14: got 'NA'
## Warning: Expecting numeric in O345 / R345C15: got 'NA'
## Warning: Expecting numeric in R345 / R345C18: got 'NA'
## Warning: Expecting numeric in S345 / R345C19: got 'NA'
## Warning: Expecting numeric in T345 / R345C20: got 'NA'
## Warning: Expecting numeric in X345 / R345C24: got 'NA'
## Warning: Expecting numeric in M346 / R346C13: got 'NA'
## Warning: Expecting numeric in N346 / R346C14: got 'NA'
## Warning: Expecting numeric in O346 / R346C15: got 'NA'
## Warning: Expecting numeric in R346 / R346C18: got 'NA'
## Warning: Expecting numeric in S346 / R346C19: got 'NA'
## Warning: Expecting numeric in T346 / R346C20: got 'NA'
## Warning: Expecting numeric in X346 / R346C24: got 'NA'
## Warning: Expecting numeric in M347 / R347C13: got 'NA'
## Warning: Expecting numeric in N347 / R347C14: got 'NA'
## Warning: Expecting numeric in O347 / R347C15: got 'NA'
## Warning: Expecting numeric in R347 / R347C18: got 'NA'
## Warning: Expecting numeric in S347 / R347C19: got 'NA'
## Warning: Expecting numeric in T347 / R347C20: got 'NA'
## Warning: Expecting numeric in X347 / R347C24: got 'NA'
## Warning: Expecting numeric in M348 / R348C13: got 'NA'
## Warning: Expecting numeric in N348 / R348C14: got 'NA'
## Warning: Expecting numeric in O348 / R348C15: got 'NA'
## Warning: Expecting numeric in R348 / R348C18: got 'NA'
## Warning: Expecting numeric in S348 / R348C19: got 'NA'
## Warning: Expecting numeric in T348 / R348C20: got 'NA'
## Warning: Expecting numeric in X348 / R348C24: got 'NA'
## Warning: Expecting numeric in M349 / R349C13: got 'NA'
## Warning: Expecting numeric in N349 / R349C14: got 'NA'
## Warning: Expecting numeric in O349 / R349C15: got 'NA'
## Warning: Expecting numeric in R349 / R349C18: got 'NA'
## Warning: Expecting numeric in S349 / R349C19: got 'NA'
## Warning: Expecting numeric in T349 / R349C20: got 'NA'
## Warning: Expecting numeric in X349 / R349C24: got 'NA'
## Warning: Expecting numeric in M350 / R350C13: got 'NA'
## Warning: Expecting numeric in N350 / R350C14: got 'NA'
## Warning: Expecting numeric in O350 / R350C15: got 'NA'
## Warning: Expecting numeric in R350 / R350C18: got 'NA'
## Warning: Expecting numeric in S350 / R350C19: got 'NA'
## Warning: Expecting numeric in T350 / R350C20: got 'NA'
## Warning: Expecting numeric in X350 / R350C24: got 'NA'
## Warning: Expecting numeric in M351 / R351C13: got 'NA'
## Warning: Expecting numeric in N351 / R351C14: got 'NA'
## Warning: Expecting numeric in O351 / R351C15: got 'NA'
## Warning: Expecting numeric in R351 / R351C18: got 'NA'
## Warning: Expecting numeric in S351 / R351C19: got 'NA'
## Warning: Expecting numeric in T351 / R351C20: got 'NA'
## Warning: Expecting numeric in X351 / R351C24: got 'NA'
## Warning: Expecting numeric in M352 / R352C13: got 'NA'
## Warning: Expecting numeric in N352 / R352C14: got 'NA'
## Warning: Expecting numeric in O352 / R352C15: got 'NA'
## Warning: Expecting numeric in R352 / R352C18: got 'NA'
## Warning: Expecting numeric in S352 / R352C19: got 'NA'
## Warning: Expecting numeric in T352 / R352C20: got 'NA'
## Warning: Expecting numeric in X352 / R352C24: got 'NA'
## Warning: Expecting numeric in M353 / R353C13: got 'NA'
## Warning: Expecting numeric in N353 / R353C14: got 'NA'
## Warning: Expecting numeric in O353 / R353C15: got 'NA'
## Warning: Expecting numeric in R353 / R353C18: got 'NA'
## Warning: Expecting numeric in S353 / R353C19: got 'NA'
## Warning: Expecting numeric in T353 / R353C20: got 'NA'
## Warning: Expecting numeric in X353 / R353C24: got 'NA'
## Warning: Expecting numeric in M354 / R354C13: got 'NA'
## Warning: Expecting numeric in N354 / R354C14: got 'NA'
## Warning: Expecting numeric in O354 / R354C15: got 'NA'
## Warning: Expecting numeric in R354 / R354C18: got 'NA'
## Warning: Expecting numeric in S354 / R354C19: got 'NA'
## Warning: Expecting numeric in T354 / R354C20: got 'NA'
## Warning: Expecting numeric in M355 / R355C13: got 'NA'
## Warning: Expecting numeric in N355 / R355C14: got 'NA'
## Warning: Expecting numeric in O355 / R355C15: got 'NA'
## Warning: Expecting numeric in R355 / R355C18: got 'NA'
## Warning: Expecting numeric in S355 / R355C19: got 'NA'
## Warning: Expecting numeric in T355 / R355C20: got 'NA'
## Warning: Expecting numeric in X355 / R355C24: got 'NA'
## Warning: Expecting numeric in M356 / R356C13: got 'NA'
## Warning: Expecting numeric in N356 / R356C14: got 'NA'
## Warning: Expecting numeric in O356 / R356C15: got 'NA'
## Warning: Expecting numeric in R356 / R356C18: got 'NA'
## Warning: Expecting numeric in S356 / R356C19: got 'NA'
## Warning: Expecting numeric in T356 / R356C20: got 'NA'
## Warning: Expecting numeric in M357 / R357C13: got 'NA'
## Warning: Expecting numeric in N357 / R357C14: got 'NA'
## Warning: Expecting numeric in O357 / R357C15: got 'NA'
## Warning: Expecting numeric in R357 / R357C18: got 'NA'
## Warning: Expecting numeric in S357 / R357C19: got 'NA'
## Warning: Expecting numeric in T357 / R357C20: got 'NA'
## Warning: Expecting numeric in M358 / R358C13: got 'NA'
## Warning: Expecting numeric in N358 / R358C14: got 'NA'
## Warning: Expecting numeric in O358 / R358C15: got 'NA'
## Warning: Expecting numeric in R358 / R358C18: got 'NA'
## Warning: Expecting numeric in S358 / R358C19: got 'NA'
## Warning: Expecting numeric in T358 / R358C20: got 'NA'
## Warning: Expecting numeric in M359 / R359C13: got 'NA'
## Warning: Expecting numeric in N359 / R359C14: got 'NA'
## Warning: Expecting numeric in O359 / R359C15: got 'NA'
## Warning: Expecting numeric in R359 / R359C18: got 'NA'
## Warning: Expecting numeric in S359 / R359C19: got 'NA'
## Warning: Expecting numeric in T359 / R359C20: got 'NA'
## Warning: Expecting numeric in M360 / R360C13: got 'NA'
## Warning: Expecting numeric in N360 / R360C14: got 'NA'
## Warning: Expecting numeric in O360 / R360C15: got 'NA'
## Warning: Expecting numeric in R360 / R360C18: got 'NA'
## Warning: Expecting numeric in S360 / R360C19: got 'NA'
## Warning: Expecting numeric in T360 / R360C20: got 'NA'
## Warning: Expecting numeric in M361 / R361C13: got 'NA'
## Warning: Expecting numeric in N361 / R361C14: got 'NA'
## Warning: Expecting numeric in O361 / R361C15: got 'NA'
## Warning: Expecting numeric in R361 / R361C18: got 'NA'
## Warning: Expecting numeric in S361 / R361C19: got 'NA'
## Warning: Expecting numeric in T361 / R361C20: got 'NA'
## Warning: Expecting numeric in X361 / R361C24: got 'NA'
## Warning: Expecting numeric in M362 / R362C13: got 'NA'
## Warning: Expecting numeric in N362 / R362C14: got 'NA'
## Warning: Expecting numeric in O362 / R362C15: got 'NA'
## Warning: Expecting numeric in R362 / R362C18: got 'NA'
## Warning: Expecting numeric in S362 / R362C19: got 'NA'
## Warning: Expecting numeric in T362 / R362C20: got 'NA'
## Warning: Expecting numeric in X362 / R362C24: got 'NA'
## Warning: Expecting numeric in M363 / R363C13: got 'NA'
## Warning: Expecting numeric in N363 / R363C14: got 'NA'
## Warning: Expecting numeric in O363 / R363C15: got 'NA'
## Warning: Expecting numeric in R363 / R363C18: got 'NA'
## Warning: Expecting numeric in S363 / R363C19: got 'NA'
## Warning: Expecting numeric in T363 / R363C20: got 'NA'
## Warning: Expecting numeric in AT363 / R363C46: got 'NA'
## Warning: Expecting numeric in M364 / R364C13: got 'NA'
## Warning: Expecting numeric in N364 / R364C14: got 'NA'
## Warning: Expecting numeric in O364 / R364C15: got 'NA'
## Warning: Expecting numeric in R364 / R364C18: got 'NA'
## Warning: Expecting numeric in S364 / R364C19: got 'NA'
## Warning: Expecting numeric in T364 / R364C20: got 'NA'
## Warning: Expecting numeric in M365 / R365C13: got 'NA'
## Warning: Expecting numeric in N365 / R365C14: got 'NA'
## Warning: Expecting numeric in O365 / R365C15: got 'NA'
## Warning: Expecting numeric in R365 / R365C18: got 'NA'
## Warning: Expecting numeric in S365 / R365C19: got 'NA'
## Warning: Expecting numeric in T365 / R365C20: got 'NA'
## Warning: Expecting numeric in M366 / R366C13: got 'NA'
## Warning: Expecting numeric in N366 / R366C14: got 'NA'
## Warning: Expecting numeric in O366 / R366C15: got 'NA'
## Warning: Expecting numeric in R366 / R366C18: got 'NA'
## Warning: Expecting numeric in S366 / R366C19: got 'NA'
## Warning: Expecting numeric in T366 / R366C20: got 'NA'
## Warning: Expecting numeric in M367 / R367C13: got 'NA'
## Warning: Expecting numeric in N367 / R367C14: got 'NA'
## Warning: Expecting numeric in O367 / R367C15: got 'NA'
## Warning: Expecting numeric in R367 / R367C18: got 'NA'
## Warning: Expecting numeric in S367 / R367C19: got 'NA'
## Warning: Expecting numeric in T367 / R367C20: got 'NA'
## Warning: Expecting numeric in M368 / R368C13: got 'NA'
## Warning: Expecting numeric in N368 / R368C14: got 'NA'
## Warning: Expecting numeric in O368 / R368C15: got 'NA'
## Warning: Expecting numeric in R368 / R368C18: got 'NA'
## Warning: Expecting numeric in S368 / R368C19: got 'NA'
## Warning: Expecting numeric in T368 / R368C20: got 'NA'
## Warning: Expecting numeric in M369 / R369C13: got 'NA'
## Warning: Expecting numeric in N369 / R369C14: got 'NA'
## Warning: Expecting numeric in O369 / R369C15: got 'NA'
## Warning: Expecting numeric in R369 / R369C18: got 'NA'
## Warning: Expecting numeric in S369 / R369C19: got 'NA'
## Warning: Expecting numeric in T369 / R369C20: got 'NA'
## Warning: Expecting numeric in M370 / R370C13: got 'NA'
## Warning: Expecting numeric in N370 / R370C14: got 'NA'
## Warning: Expecting numeric in O370 / R370C15: got 'NA'
## Warning: Expecting numeric in R370 / R370C18: got 'NA'
## Warning: Expecting numeric in S370 / R370C19: got 'NA'
## Warning: Expecting numeric in T370 / R370C20: got 'NA'
## Warning: Expecting numeric in M371 / R371C13: got 'NA'
## Warning: Expecting numeric in N371 / R371C14: got 'NA'
## Warning: Expecting numeric in O371 / R371C15: got 'NA'
## Warning: Expecting numeric in R371 / R371C18: got 'NA'
## Warning: Expecting numeric in S371 / R371C19: got 'NA'
## Warning: Expecting numeric in T371 / R371C20: got 'NA'
## Warning: Expecting numeric in M372 / R372C13: got 'NA'
## Warning: Expecting numeric in N372 / R372C14: got 'NA'
## Warning: Expecting numeric in O372 / R372C15: got 'NA'
## Warning: Expecting numeric in R372 / R372C18: got 'NA'
## Warning: Expecting numeric in S372 / R372C19: got 'NA'
## Warning: Expecting numeric in T372 / R372C20: got 'NA'
## Warning: Expecting numeric in M373 / R373C13: got 'NA'
## Warning: Expecting numeric in N373 / R373C14: got 'NA'
## Warning: Expecting numeric in O373 / R373C15: got 'NA'
## Warning: Expecting numeric in R373 / R373C18: got 'NA'
## Warning: Expecting numeric in S373 / R373C19: got 'NA'
## Warning: Expecting numeric in T373 / R373C20: got 'NA'
## Warning: Expecting numeric in M374 / R374C13: got 'NA'
## Warning: Expecting numeric in N374 / R374C14: got 'NA'
## Warning: Expecting numeric in O374 / R374C15: got 'NA'
## Warning: Expecting numeric in R374 / R374C18: got 'NA'
## Warning: Expecting numeric in S374 / R374C19: got 'NA'
## Warning: Expecting numeric in T374 / R374C20: got 'NA'
## Warning: Expecting numeric in M375 / R375C13: got 'NA'
## Warning: Expecting numeric in N375 / R375C14: got 'NA'
## Warning: Expecting numeric in O375 / R375C15: got 'NA'
## Warning: Expecting numeric in R375 / R375C18: got 'NA'
## Warning: Expecting numeric in S375 / R375C19: got 'NA'
## Warning: Expecting numeric in T375 / R375C20: got 'NA'
## Warning: Expecting numeric in M376 / R376C13: got 'NA'
## Warning: Expecting numeric in N376 / R376C14: got 'NA'
## Warning: Expecting numeric in O376 / R376C15: got 'NA'
## Warning: Expecting numeric in R376 / R376C18: got 'NA'
## Warning: Expecting numeric in S376 / R376C19: got 'NA'
## Warning: Expecting numeric in T376 / R376C20: got 'NA'
## Warning: Expecting numeric in M377 / R377C13: got 'NA'
## Warning: Expecting numeric in N377 / R377C14: got 'NA'
## Warning: Expecting numeric in O377 / R377C15: got 'NA'
## Warning: Expecting numeric in R377 / R377C18: got 'NA'
## Warning: Expecting numeric in S377 / R377C19: got 'NA'
## Warning: Expecting numeric in T377 / R377C20: got 'NA'
## Warning: Expecting numeric in M378 / R378C13: got 'NA'
## Warning: Expecting numeric in N378 / R378C14: got 'NA'
## Warning: Expecting numeric in O378 / R378C15: got 'NA'
## Warning: Expecting numeric in R378 / R378C18: got 'NA'
## Warning: Expecting numeric in S378 / R378C19: got 'NA'
## Warning: Expecting numeric in T378 / R378C20: got 'NA'
## Warning: Expecting numeric in M379 / R379C13: got 'NA'
## Warning: Expecting numeric in N379 / R379C14: got 'NA'
## Warning: Expecting numeric in O379 / R379C15: got 'NA'
## Warning: Expecting numeric in R379 / R379C18: got 'NA'
## Warning: Expecting numeric in S379 / R379C19: got 'NA'
## Warning: Expecting numeric in T379 / R379C20: got 'NA'
## Warning: Expecting numeric in M380 / R380C13: got 'NA'
## Warning: Expecting numeric in N380 / R380C14: got 'NA'
## Warning: Expecting numeric in O380 / R380C15: got 'NA'
## Warning: Expecting numeric in R380 / R380C18: got 'NA'
## Warning: Expecting numeric in S380 / R380C19: got 'NA'
## Warning: Expecting numeric in T380 / R380C20: got 'NA'
## Warning: Expecting numeric in M381 / R381C13: got 'NA'
## Warning: Expecting numeric in N381 / R381C14: got 'NA'
## Warning: Expecting numeric in O381 / R381C15: got 'NA'
## Warning: Expecting numeric in R381 / R381C18: got 'NA'
## Warning: Expecting numeric in S381 / R381C19: got 'NA'
## Warning: Expecting numeric in T381 / R381C20: got 'NA'
## Warning: Expecting numeric in M382 / R382C13: got 'NA'
## Warning: Expecting numeric in N382 / R382C14: got 'NA'
## Warning: Expecting numeric in O382 / R382C15: got 'NA'
## Warning: Expecting numeric in R382 / R382C18: got 'NA'
## Warning: Expecting numeric in S382 / R382C19: got 'NA'
## Warning: Expecting numeric in T382 / R382C20: got 'NA'
## Warning: Expecting numeric in M383 / R383C13: got 'NA'
## Warning: Expecting numeric in N383 / R383C14: got 'NA'
## Warning: Expecting numeric in O383 / R383C15: got 'NA'
## Warning: Expecting numeric in R383 / R383C18: got 'NA'
## Warning: Expecting numeric in S383 / R383C19: got 'NA'
## Warning: Expecting numeric in T383 / R383C20: got 'NA'
## Warning: Expecting numeric in M384 / R384C13: got 'NA'
## Warning: Expecting numeric in N384 / R384C14: got 'NA'
## Warning: Expecting numeric in O384 / R384C15: got 'NA'
## Warning: Expecting numeric in R384 / R384C18: got 'NA'
## Warning: Expecting numeric in S384 / R384C19: got 'NA'
## Warning: Expecting numeric in T384 / R384C20: got 'NA'
## Warning: Expecting numeric in M385 / R385C13: got 'NA'
## Warning: Expecting numeric in N385 / R385C14: got 'NA'
## Warning: Expecting numeric in O385 / R385C15: got 'NA'
## Warning: Expecting numeric in R385 / R385C18: got 'NA'
## Warning: Expecting numeric in S385 / R385C19: got 'NA'
## Warning: Expecting numeric in T385 / R385C20: got 'NA'
## Warning: Expecting numeric in M386 / R386C13: got 'NA'
## Warning: Expecting numeric in N386 / R386C14: got 'NA'
## Warning: Expecting numeric in O386 / R386C15: got 'NA'
## Warning: Expecting numeric in R386 / R386C18: got 'NA'
## Warning: Expecting numeric in S386 / R386C19: got 'NA'
## Warning: Expecting numeric in T386 / R386C20: got 'NA'
## Warning: Expecting numeric in M387 / R387C13: got 'NA'
## Warning: Expecting numeric in N387 / R387C14: got 'NA'
## Warning: Expecting numeric in O387 / R387C15: got 'NA'
## Warning: Expecting numeric in R387 / R387C18: got 'NA'
## Warning: Expecting numeric in S387 / R387C19: got 'NA'
## Warning: Expecting numeric in T387 / R387C20: got 'NA'
## Warning: Expecting numeric in M388 / R388C13: got 'NA'
## Warning: Expecting numeric in N388 / R388C14: got 'NA'
## Warning: Expecting numeric in O388 / R388C15: got 'NA'
## Warning: Expecting numeric in R388 / R388C18: got 'NA'
## Warning: Expecting numeric in S388 / R388C19: got 'NA'
## Warning: Expecting numeric in T388 / R388C20: got 'NA'
## Warning: Expecting numeric in M389 / R389C13: got 'NA'
## Warning: Expecting numeric in N389 / R389C14: got 'NA'
## Warning: Expecting numeric in O389 / R389C15: got 'NA'
## Warning: Expecting numeric in R389 / R389C18: got 'NA'
## Warning: Expecting numeric in S389 / R389C19: got 'NA'
## Warning: Expecting numeric in T389 / R389C20: got 'NA'
## Warning: Expecting numeric in M390 / R390C13: got 'NA'
## Warning: Expecting numeric in N390 / R390C14: got 'NA'
## Warning: Expecting numeric in O390 / R390C15: got 'NA'
## Warning: Expecting numeric in R390 / R390C18: got 'NA'
## Warning: Expecting numeric in S390 / R390C19: got 'NA'
## Warning: Expecting numeric in T390 / R390C20: got 'NA'
## Warning: Expecting numeric in M391 / R391C13: got 'NA'
## Warning: Expecting numeric in N391 / R391C14: got 'NA'
## Warning: Expecting numeric in O391 / R391C15: got 'NA'
## Warning: Expecting numeric in R391 / R391C18: got 'NA'
## Warning: Expecting numeric in S391 / R391C19: got 'NA'
## Warning: Expecting numeric in T391 / R391C20: got 'NA'
## Warning: Expecting numeric in M392 / R392C13: got 'NA'
## Warning: Expecting numeric in N392 / R392C14: got 'NA'
## Warning: Expecting numeric in O392 / R392C15: got 'NA'
## Warning: Expecting numeric in R392 / R392C18: got 'NA'
## Warning: Expecting numeric in S392 / R392C19: got 'NA'
## Warning: Expecting numeric in T392 / R392C20: got 'NA'
## Warning: Expecting numeric in M393 / R393C13: got 'NA'
## Warning: Expecting numeric in N393 / R393C14: got 'NA'
## Warning: Expecting numeric in O393 / R393C15: got 'NA'
## Warning: Expecting numeric in R393 / R393C18: got 'NA'
## Warning: Expecting numeric in S393 / R393C19: got 'NA'
## Warning: Expecting numeric in T393 / R393C20: got 'NA'
## Warning: Expecting numeric in M394 / R394C13: got 'NA'
## Warning: Expecting numeric in N394 / R394C14: got 'NA'
## Warning: Expecting numeric in O394 / R394C15: got 'NA'
## Warning: Expecting numeric in R394 / R394C18: got 'NA'
## Warning: Expecting numeric in S394 / R394C19: got 'NA'
## Warning: Expecting numeric in T394 / R394C20: got 'NA'
## Warning: Expecting numeric in M395 / R395C13: got 'NA'
## Warning: Expecting numeric in N395 / R395C14: got 'NA'
## Warning: Expecting numeric in O395 / R395C15: got 'NA'
## Warning: Expecting numeric in R395 / R395C18: got 'NA'
## Warning: Expecting numeric in S395 / R395C19: got 'NA'
## Warning: Expecting numeric in T395 / R395C20: got 'NA'
## Warning: Expecting numeric in M396 / R396C13: got 'NA'
## Warning: Expecting numeric in N396 / R396C14: got 'NA'
## Warning: Expecting numeric in O396 / R396C15: got 'NA'
## Warning: Expecting numeric in R396 / R396C18: got 'NA'
## Warning: Expecting numeric in S396 / R396C19: got 'NA'
## Warning: Expecting numeric in T396 / R396C20: got 'NA'
## Warning: Expecting numeric in M397 / R397C13: got 'NA'
## Warning: Expecting numeric in N397 / R397C14: got 'NA'
## Warning: Expecting numeric in O397 / R397C15: got 'NA'
## Warning: Expecting numeric in R397 / R397C18: got 'NA'
## Warning: Expecting numeric in S397 / R397C19: got 'NA'
## Warning: Expecting numeric in T397 / R397C20: got 'NA'
## Warning: Expecting numeric in M398 / R398C13: got 'NA'
## Warning: Expecting numeric in N398 / R398C14: got 'NA'
## Warning: Expecting numeric in O398 / R398C15: got 'NA'
## Warning: Expecting numeric in R398 / R398C18: got 'NA'
## Warning: Expecting numeric in S398 / R398C19: got 'NA'
## Warning: Expecting numeric in T398 / R398C20: got 'NA'
## Warning: Expecting numeric in M399 / R399C13: got 'NA'
## Warning: Expecting numeric in N399 / R399C14: got 'NA'
## Warning: Expecting numeric in O399 / R399C15: got 'NA'
## Warning: Expecting numeric in R399 / R399C18: got 'NA'
## Warning: Expecting numeric in S399 / R399C19: got 'NA'
## Warning: Expecting numeric in T399 / R399C20: got 'NA'
## Warning: Expecting numeric in M400 / R400C13: got 'NA'
## Warning: Expecting numeric in N400 / R400C14: got 'NA'
## Warning: Expecting numeric in O400 / R400C15: got 'NA'
## Warning: Expecting numeric in R400 / R400C18: got 'NA'
## Warning: Expecting numeric in S400 / R400C19: got 'NA'
## Warning: Expecting numeric in T400 / R400C20: got 'NA'
## Warning: Expecting numeric in M401 / R401C13: got 'NA'
## Warning: Expecting numeric in N401 / R401C14: got 'NA'
## Warning: Expecting numeric in O401 / R401C15: got 'NA'
## Warning: Expecting numeric in R401 / R401C18: got 'NA'
## Warning: Expecting numeric in S401 / R401C19: got 'NA'
## Warning: Expecting numeric in T401 / R401C20: got 'NA'
## Warning: Expecting numeric in M402 / R402C13: got 'NA'
## Warning: Expecting numeric in N402 / R402C14: got 'NA'
## Warning: Expecting numeric in O402 / R402C15: got 'NA'
## Warning: Expecting numeric in R402 / R402C18: got 'NA'
## Warning: Expecting numeric in S402 / R402C19: got 'NA'
## Warning: Expecting numeric in T402 / R402C20: got 'NA'
## Warning: Expecting numeric in M403 / R403C13: got 'NA'
## Warning: Expecting numeric in N403 / R403C14: got 'NA'
## Warning: Expecting numeric in O403 / R403C15: got 'NA'
## Warning: Expecting numeric in R403 / R403C18: got 'NA'
## Warning: Expecting numeric in S403 / R403C19: got 'NA'
## Warning: Expecting numeric in T403 / R403C20: got 'NA'
## Warning: Expecting numeric in M404 / R404C13: got 'NA'
## Warning: Expecting numeric in N404 / R404C14: got 'NA'
## Warning: Expecting numeric in O404 / R404C15: got 'NA'
## Warning: Expecting numeric in R404 / R404C18: got 'NA'
## Warning: Expecting numeric in S404 / R404C19: got 'NA'
## Warning: Expecting numeric in T404 / R404C20: got 'NA'
## Warning: Expecting numeric in M405 / R405C13: got 'NA'
## Warning: Expecting numeric in N405 / R405C14: got 'NA'
## Warning: Expecting numeric in O405 / R405C15: got 'NA'
## Warning: Expecting numeric in R405 / R405C18: got 'NA'
## Warning: Expecting numeric in S405 / R405C19: got 'NA'
## Warning: Expecting numeric in T405 / R405C20: got 'NA'
## Warning: Expecting numeric in M406 / R406C13: got 'NA'
## Warning: Expecting numeric in N406 / R406C14: got 'NA'
## Warning: Expecting numeric in O406 / R406C15: got 'NA'
## Warning: Expecting numeric in R406 / R406C18: got 'NA'
## Warning: Expecting numeric in S406 / R406C19: got 'NA'
## Warning: Expecting numeric in T406 / R406C20: got 'NA'
## Warning: Expecting numeric in M407 / R407C13: got 'NA'
## Warning: Expecting numeric in N407 / R407C14: got 'NA'
## Warning: Expecting numeric in O407 / R407C15: got 'NA'
## Warning: Expecting numeric in R407 / R407C18: got 'NA'
## Warning: Expecting numeric in S407 / R407C19: got 'NA'
## Warning: Expecting numeric in T407 / R407C20: got 'NA'
## Warning: Expecting numeric in M408 / R408C13: got 'NA'
## Warning: Expecting numeric in N408 / R408C14: got 'NA'
## Warning: Expecting numeric in O408 / R408C15: got 'NA'
## Warning: Expecting numeric in R408 / R408C18: got 'NA'
## Warning: Expecting numeric in S408 / R408C19: got 'NA'
## Warning: Expecting numeric in T408 / R408C20: got 'NA'
## Warning: Expecting numeric in M409 / R409C13: got 'NA'
## Warning: Expecting numeric in N409 / R409C14: got 'NA'
## Warning: Expecting numeric in O409 / R409C15: got 'NA'
## Warning: Expecting numeric in R409 / R409C18: got 'NA'
## Warning: Expecting numeric in S409 / R409C19: got 'NA'
## Warning: Expecting numeric in T409 / R409C20: got 'NA'
## Warning: Expecting numeric in M410 / R410C13: got 'NA'
## Warning: Expecting numeric in N410 / R410C14: got 'NA'
## Warning: Expecting numeric in O410 / R410C15: got 'NA'
## Warning: Expecting numeric in R410 / R410C18: got 'NA'
## Warning: Expecting numeric in S410 / R410C19: got 'NA'
## Warning: Expecting numeric in T410 / R410C20: got 'NA'
## Warning: Expecting numeric in M411 / R411C13: got 'NA'
## Warning: Expecting numeric in N411 / R411C14: got 'NA'
## Warning: Expecting numeric in O411 / R411C15: got 'NA'
## Warning: Expecting numeric in R411 / R411C18: got 'NA'
## Warning: Expecting numeric in S411 / R411C19: got 'NA'
## Warning: Expecting numeric in T411 / R411C20: got 'NA'
## Warning: Expecting numeric in M412 / R412C13: got 'NA'
## Warning: Expecting numeric in N412 / R412C14: got 'NA'
## Warning: Expecting numeric in O412 / R412C15: got 'NA'
## Warning: Expecting numeric in R412 / R412C18: got 'NA'
## Warning: Expecting numeric in S412 / R412C19: got 'NA'
## Warning: Expecting numeric in T412 / R412C20: got 'NA'
## Warning: Expecting numeric in M413 / R413C13: got 'NA'
## Warning: Expecting numeric in N413 / R413C14: got 'NA'
## Warning: Expecting numeric in O413 / R413C15: got 'NA'
## Warning: Expecting numeric in R413 / R413C18: got 'NA'
## Warning: Expecting numeric in S413 / R413C19: got 'NA'
## Warning: Expecting numeric in T413 / R413C20: got 'NA'
## Warning: Expecting numeric in M414 / R414C13: got 'NA'
## Warning: Expecting numeric in N414 / R414C14: got 'NA'
## Warning: Expecting numeric in O414 / R414C15: got 'NA'
## Warning: Expecting numeric in R414 / R414C18: got 'NA'
## Warning: Expecting numeric in S414 / R414C19: got 'NA'
## Warning: Expecting numeric in T414 / R414C20: got 'NA'
## Warning: Expecting numeric in M415 / R415C13: got 'NA'
## Warning: Expecting numeric in N415 / R415C14: got 'NA'
## Warning: Expecting numeric in O415 / R415C15: got 'NA'
## Warning: Expecting numeric in R415 / R415C18: got 'NA'
## Warning: Expecting numeric in S415 / R415C19: got 'NA'
## Warning: Expecting numeric in T415 / R415C20: got 'NA'
## Warning: Expecting numeric in M416 / R416C13: got 'NA'
## Warning: Expecting numeric in N416 / R416C14: got 'NA'
## Warning: Expecting numeric in O416 / R416C15: got 'NA'
## Warning: Expecting numeric in R416 / R416C18: got 'NA'
## Warning: Expecting numeric in S416 / R416C19: got 'NA'
## Warning: Expecting numeric in T416 / R416C20: got 'NA'
## Warning: Expecting numeric in M417 / R417C13: got 'NA'
## Warning: Expecting numeric in N417 / R417C14: got 'NA'
## Warning: Expecting numeric in O417 / R417C15: got 'NA'
## Warning: Expecting numeric in R417 / R417C18: got 'NA'
## Warning: Expecting numeric in S417 / R417C19: got 'NA'
## Warning: Expecting numeric in T417 / R417C20: got 'NA'
## Warning: Expecting numeric in M418 / R418C13: got 'NA'
## Warning: Expecting numeric in N418 / R418C14: got 'NA'
## Warning: Expecting numeric in O418 / R418C15: got 'NA'
## Warning: Expecting numeric in R418 / R418C18: got 'NA'
## Warning: Expecting numeric in S418 / R418C19: got 'NA'
## Warning: Expecting numeric in T418 / R418C20: got 'NA'
## Warning: Expecting numeric in M419 / R419C13: got 'NA'
## Warning: Expecting numeric in N419 / R419C14: got 'NA'
## Warning: Expecting numeric in O419 / R419C15: got 'NA'
## Warning: Expecting numeric in R419 / R419C18: got 'NA'
## Warning: Expecting numeric in S419 / R419C19: got 'NA'
## Warning: Expecting numeric in T419 / R419C20: got 'NA'
## Warning: Expecting numeric in M420 / R420C13: got 'NA'
## Warning: Expecting numeric in N420 / R420C14: got 'NA'
## Warning: Expecting numeric in O420 / R420C15: got 'NA'
## Warning: Expecting numeric in R420 / R420C18: got 'NA'
## Warning: Expecting numeric in S420 / R420C19: got 'NA'
## Warning: Expecting numeric in T420 / R420C20: got 'NA'
## Warning: Expecting numeric in M421 / R421C13: got 'NA'
## Warning: Expecting numeric in N421 / R421C14: got 'NA'
## Warning: Expecting numeric in O421 / R421C15: got 'NA'
## Warning: Expecting numeric in R421 / R421C18: got 'NA'
## Warning: Expecting numeric in S421 / R421C19: got 'NA'
## Warning: Expecting numeric in T421 / R421C20: got 'NA'
## Warning: Expecting numeric in M422 / R422C13: got 'NA'
## Warning: Expecting numeric in N422 / R422C14: got 'NA'
## Warning: Expecting numeric in O422 / R422C15: got 'NA'
## Warning: Expecting numeric in R422 / R422C18: got 'NA'
## Warning: Expecting numeric in S422 / R422C19: got 'NA'
## Warning: Expecting numeric in T422 / R422C20: got 'NA'
## Warning: Expecting numeric in M423 / R423C13: got 'NA'
## Warning: Expecting numeric in N423 / R423C14: got 'NA'
## Warning: Expecting numeric in O423 / R423C15: got 'NA'
## Warning: Expecting numeric in R423 / R423C18: got 'NA'
## Warning: Expecting numeric in S423 / R423C19: got 'NA'
## Warning: Expecting numeric in T423 / R423C20: got 'NA'
## Warning: Expecting numeric in M424 / R424C13: got 'NA'
## Warning: Expecting numeric in N424 / R424C14: got 'NA'
## Warning: Expecting numeric in O424 / R424C15: got 'NA'
## Warning: Expecting numeric in R424 / R424C18: got 'NA'
## Warning: Expecting numeric in S424 / R424C19: got 'NA'
## Warning: Expecting numeric in T424 / R424C20: got 'NA'
## Warning: Expecting numeric in M425 / R425C13: got 'NA'
## Warning: Expecting numeric in N425 / R425C14: got 'NA'
## Warning: Expecting numeric in O425 / R425C15: got 'NA'
## Warning: Expecting numeric in R425 / R425C18: got 'NA'
## Warning: Expecting numeric in S425 / R425C19: got 'NA'
## Warning: Expecting numeric in T425 / R425C20: got 'NA'
## Warning: Expecting numeric in M426 / R426C13: got 'NA'
## Warning: Expecting numeric in N426 / R426C14: got 'NA'
## Warning: Expecting numeric in O426 / R426C15: got 'NA'
## Warning: Expecting numeric in R426 / R426C18: got 'NA'
## Warning: Expecting numeric in S426 / R426C19: got 'NA'
## Warning: Expecting numeric in T426 / R426C20: got 'NA'
## Warning: Expecting numeric in M427 / R427C13: got 'NA'
## Warning: Expecting numeric in N427 / R427C14: got 'NA'
## Warning: Expecting numeric in O427 / R427C15: got 'NA'
## Warning: Expecting numeric in R427 / R427C18: got 'NA'
## Warning: Expecting numeric in S427 / R427C19: got 'NA'
## Warning: Expecting numeric in T427 / R427C20: got 'NA'
## Warning: Expecting numeric in M428 / R428C13: got 'NA'
## Warning: Expecting numeric in N428 / R428C14: got 'NA'
## Warning: Expecting numeric in O428 / R428C15: got 'NA'
## Warning: Expecting numeric in R428 / R428C18: got 'NA'
## Warning: Expecting numeric in S428 / R428C19: got 'NA'
## Warning: Expecting numeric in T428 / R428C20: got 'NA'
## Warning: Expecting numeric in M429 / R429C13: got 'NA'
## Warning: Expecting numeric in N429 / R429C14: got 'NA'
## Warning: Expecting numeric in O429 / R429C15: got 'NA'
## Warning: Expecting numeric in R429 / R429C18: got 'NA'
## Warning: Expecting numeric in S429 / R429C19: got 'NA'
## Warning: Expecting numeric in T429 / R429C20: got 'NA'
## Warning: Expecting numeric in M430 / R430C13: got 'NA'
## Warning: Expecting numeric in N430 / R430C14: got 'NA'
## Warning: Expecting numeric in O430 / R430C15: got 'NA'
## Warning: Expecting numeric in R430 / R430C18: got 'NA'
## Warning: Expecting numeric in S430 / R430C19: got 'NA'
## Warning: Expecting numeric in T430 / R430C20: got 'NA'
## Warning: Expecting numeric in M431 / R431C13: got 'NA'
## Warning: Expecting numeric in N431 / R431C14: got 'NA'
## Warning: Expecting numeric in O431 / R431C15: got 'NA'
## Warning: Expecting numeric in R431 / R431C18: got 'NA'
## Warning: Expecting numeric in S431 / R431C19: got 'NA'
## Warning: Expecting numeric in T431 / R431C20: got 'NA'
## Warning: Expecting numeric in M432 / R432C13: got 'NA'
## Warning: Expecting numeric in N432 / R432C14: got 'NA'
## Warning: Expecting numeric in O432 / R432C15: got 'NA'
## Warning: Expecting numeric in R432 / R432C18: got 'NA'
## Warning: Expecting numeric in S432 / R432C19: got 'NA'
## Warning: Expecting numeric in T432 / R432C20: got 'NA'
## Warning: Expecting numeric in M433 / R433C13: got 'NA'
## Warning: Expecting numeric in N433 / R433C14: got 'NA'
## Warning: Expecting numeric in O433 / R433C15: got 'NA'
## Warning: Expecting numeric in R433 / R433C18: got 'NA'
## Warning: Expecting numeric in S433 / R433C19: got 'NA'
## Warning: Expecting numeric in T433 / R433C20: got 'NA'
## Warning: Expecting numeric in M434 / R434C13: got 'NA'
## Warning: Expecting numeric in N434 / R434C14: got 'NA'
## Warning: Expecting numeric in O434 / R434C15: got 'NA'
## Warning: Expecting numeric in R434 / R434C18: got 'NA'
## Warning: Expecting numeric in S434 / R434C19: got 'NA'
## Warning: Expecting numeric in T434 / R434C20: got 'NA'
## Warning: Expecting numeric in M435 / R435C13: got 'NA'
## Warning: Expecting numeric in N435 / R435C14: got 'NA'
## Warning: Expecting numeric in O435 / R435C15: got 'NA'
## Warning: Expecting numeric in R435 / R435C18: got 'NA'
## Warning: Expecting numeric in S435 / R435C19: got 'NA'
## Warning: Expecting numeric in T435 / R435C20: got 'NA'
## Warning: Expecting numeric in M436 / R436C13: got 'NA'
## Warning: Expecting numeric in N436 / R436C14: got 'NA'
## Warning: Expecting numeric in O436 / R436C15: got 'NA'
## Warning: Expecting numeric in R436 / R436C18: got 'NA'
## Warning: Expecting numeric in S436 / R436C19: got 'NA'
## Warning: Expecting numeric in T436 / R436C20: got 'NA'
## Warning: Expecting numeric in M437 / R437C13: got 'NA'
## Warning: Expecting numeric in N437 / R437C14: got 'NA'
## Warning: Expecting numeric in O437 / R437C15: got 'NA'
## Warning: Expecting numeric in R437 / R437C18: got 'NA'
## Warning: Expecting numeric in S437 / R437C19: got 'NA'
## Warning: Expecting numeric in T437 / R437C20: got 'NA'
## Warning: Expecting numeric in M438 / R438C13: got 'NA'
## Warning: Expecting numeric in N438 / R438C14: got 'NA'
## Warning: Expecting numeric in O438 / R438C15: got 'NA'
## Warning: Expecting numeric in R438 / R438C18: got 'NA'
## Warning: Expecting numeric in S438 / R438C19: got 'NA'
## Warning: Expecting numeric in T438 / R438C20: got 'NA'
## Warning: Expecting numeric in M439 / R439C13: got 'NA'
## Warning: Expecting numeric in N439 / R439C14: got 'NA'
## Warning: Expecting numeric in O439 / R439C15: got 'NA'
## Warning: Expecting numeric in R439 / R439C18: got 'NA'
## Warning: Expecting numeric in S439 / R439C19: got 'NA'
## Warning: Expecting numeric in T439 / R439C20: got 'NA'
## Warning: Expecting numeric in M440 / R440C13: got 'NA'
## Warning: Expecting numeric in N440 / R440C14: got 'NA'
## Warning: Expecting numeric in O440 / R440C15: got 'NA'
## Warning: Expecting numeric in R440 / R440C18: got 'NA'
## Warning: Expecting numeric in S440 / R440C19: got 'NA'
## Warning: Expecting numeric in T440 / R440C20: got 'NA'
## Warning: Expecting numeric in M441 / R441C13: got 'NA'
## Warning: Expecting numeric in N441 / R441C14: got 'NA'
## Warning: Expecting numeric in O441 / R441C15: got 'NA'
## Warning: Expecting numeric in R441 / R441C18: got 'NA'
## Warning: Expecting numeric in S441 / R441C19: got 'NA'
## Warning: Expecting numeric in T441 / R441C20: got 'NA'
## Warning: Expecting numeric in M442 / R442C13: got 'NA'
## Warning: Expecting numeric in N442 / R442C14: got 'NA'
## Warning: Expecting numeric in O442 / R442C15: got 'NA'
## Warning: Expecting numeric in R442 / R442C18: got 'NA'
## Warning: Expecting numeric in S442 / R442C19: got 'NA'
## Warning: Expecting numeric in T442 / R442C20: got 'NA'
## Warning: Expecting numeric in M443 / R443C13: got 'NA'
## Warning: Expecting numeric in N443 / R443C14: got 'NA'
## Warning: Expecting numeric in O443 / R443C15: got 'NA'
## Warning: Expecting numeric in R443 / R443C18: got 'NA'
## Warning: Expecting numeric in S443 / R443C19: got 'NA'
## Warning: Expecting numeric in T443 / R443C20: got 'NA'
## Warning: Expecting numeric in M444 / R444C13: got 'NA'
## Warning: Expecting numeric in N444 / R444C14: got 'NA'
## Warning: Expecting numeric in O444 / R444C15: got 'NA'
## Warning: Expecting numeric in R444 / R444C18: got 'NA'
## Warning: Expecting numeric in S444 / R444C19: got 'NA'
## Warning: Expecting numeric in T444 / R444C20: got 'NA'
## Warning: Expecting numeric in M445 / R445C13: got 'NA'
## Warning: Expecting numeric in N445 / R445C14: got 'NA'
## Warning: Expecting numeric in O445 / R445C15: got 'NA'
## Warning: Expecting numeric in R445 / R445C18: got 'NA'
## Warning: Expecting numeric in S445 / R445C19: got 'NA'
## Warning: Expecting numeric in T445 / R445C20: got 'NA'
## Warning: Expecting numeric in M446 / R446C13: got 'NA'
## Warning: Expecting numeric in N446 / R446C14: got 'NA'
## Warning: Expecting numeric in O446 / R446C15: got 'NA'
## Warning: Expecting numeric in R446 / R446C18: got 'NA'
## Warning: Expecting numeric in S446 / R446C19: got 'NA'
## Warning: Expecting numeric in T446 / R446C20: got 'NA'
## Warning: Expecting numeric in M447 / R447C13: got 'NA'
## Warning: Expecting numeric in N447 / R447C14: got 'NA'
## Warning: Expecting numeric in O447 / R447C15: got 'NA'
## Warning: Expecting numeric in R447 / R447C18: got 'NA'
## Warning: Expecting numeric in S447 / R447C19: got 'NA'
## Warning: Expecting numeric in T447 / R447C20: got 'NA'
## Warning: Expecting numeric in M448 / R448C13: got 'NA'
## Warning: Expecting numeric in N448 / R448C14: got 'NA'
## Warning: Expecting numeric in O448 / R448C15: got 'NA'
## Warning: Expecting numeric in R448 / R448C18: got 'NA'
## Warning: Expecting numeric in S448 / R448C19: got 'NA'
## Warning: Expecting numeric in T448 / R448C20: got 'NA'
## Warning: Expecting numeric in M449 / R449C13: got 'NA'
## Warning: Expecting numeric in N449 / R449C14: got 'NA'
## Warning: Expecting numeric in O449 / R449C15: got 'NA'
## Warning: Expecting numeric in R449 / R449C18: got 'NA'
## Warning: Expecting numeric in S449 / R449C19: got 'NA'
## Warning: Expecting numeric in T449 / R449C20: got 'NA'
## Warning: Expecting numeric in M450 / R450C13: got 'NA'
## Warning: Expecting numeric in N450 / R450C14: got 'NA'
## Warning: Expecting numeric in O450 / R450C15: got 'NA'
## Warning: Expecting numeric in R450 / R450C18: got 'NA'
## Warning: Expecting numeric in S450 / R450C19: got 'NA'
## Warning: Expecting numeric in T450 / R450C20: got 'NA'
## Warning: Expecting numeric in M451 / R451C13: got 'NA'
## Warning: Expecting numeric in N451 / R451C14: got 'NA'
## Warning: Expecting numeric in O451 / R451C15: got 'NA'
## Warning: Expecting numeric in R451 / R451C18: got 'NA'
## Warning: Expecting numeric in S451 / R451C19: got 'NA'
## Warning: Expecting numeric in T451 / R451C20: got 'NA'
## Warning: Expecting numeric in M452 / R452C13: got 'NA'
## Warning: Expecting numeric in N452 / R452C14: got 'NA'
## Warning: Expecting numeric in O452 / R452C15: got 'NA'
## Warning: Expecting numeric in R452 / R452C18: got 'NA'
## Warning: Expecting numeric in S452 / R452C19: got 'NA'
## Warning: Expecting numeric in T452 / R452C20: got 'NA'
## Warning: Expecting numeric in M453 / R453C13: got 'NA'
## Warning: Expecting numeric in N453 / R453C14: got 'NA'
## Warning: Expecting numeric in O453 / R453C15: got 'NA'
## Warning: Expecting numeric in R453 / R453C18: got 'NA'
## Warning: Expecting numeric in S453 / R453C19: got 'NA'
## Warning: Expecting numeric in T453 / R453C20: got 'NA'
## Warning: Expecting numeric in M454 / R454C13: got 'NA'
## Warning: Expecting numeric in N454 / R454C14: got 'NA'
## Warning: Expecting numeric in O454 / R454C15: got 'NA'
## Warning: Expecting numeric in R454 / R454C18: got 'NA'
## Warning: Expecting numeric in S454 / R454C19: got 'NA'
## Warning: Expecting numeric in T454 / R454C20: got 'NA'
## Warning: Expecting numeric in M455 / R455C13: got 'NA'
## Warning: Expecting numeric in N455 / R455C14: got 'NA'
## Warning: Expecting numeric in O455 / R455C15: got 'NA'
## Warning: Expecting numeric in R455 / R455C18: got 'NA'
## Warning: Expecting numeric in S455 / R455C19: got 'NA'
## Warning: Expecting numeric in T455 / R455C20: got 'NA'
## Warning: Expecting numeric in M456 / R456C13: got 'NA'
## Warning: Expecting numeric in N456 / R456C14: got 'NA'
## Warning: Expecting numeric in O456 / R456C15: got 'NA'
## Warning: Expecting numeric in R456 / R456C18: got 'NA'
## Warning: Expecting numeric in S456 / R456C19: got 'NA'
## Warning: Expecting numeric in T456 / R456C20: got 'NA'
## Warning: Expecting numeric in M457 / R457C13: got 'NA'
## Warning: Expecting numeric in N457 / R457C14: got 'NA'
## Warning: Expecting numeric in O457 / R457C15: got 'NA'
## Warning: Expecting numeric in R457 / R457C18: got 'NA'
## Warning: Expecting numeric in S457 / R457C19: got 'NA'
## Warning: Expecting numeric in T457 / R457C20: got 'NA'
## Warning: Expecting numeric in M458 / R458C13: got 'NA'
## Warning: Expecting numeric in N458 / R458C14: got 'NA'
## Warning: Expecting numeric in O458 / R458C15: got 'NA'
## Warning: Expecting numeric in R458 / R458C18: got 'NA'
## Warning: Expecting numeric in S458 / R458C19: got 'NA'
## Warning: Expecting numeric in T458 / R458C20: got 'NA'
## Warning: Expecting numeric in M459 / R459C13: got 'NA'
## Warning: Expecting numeric in N459 / R459C14: got 'NA'
## Warning: Expecting numeric in O459 / R459C15: got 'NA'
## Warning: Expecting numeric in R459 / R459C18: got 'NA'
## Warning: Expecting numeric in S459 / R459C19: got 'NA'
## Warning: Expecting numeric in T459 / R459C20: got 'NA'
## Warning: Expecting numeric in M460 / R460C13: got 'NA'
## Warning: Expecting numeric in N460 / R460C14: got 'NA'
## Warning: Expecting numeric in O460 / R460C15: got 'NA'
## Warning: Expecting numeric in R460 / R460C18: got 'NA'
## Warning: Expecting numeric in S460 / R460C19: got 'NA'
## Warning: Expecting numeric in T460 / R460C20: got 'NA'
## Warning: Expecting numeric in M461 / R461C13: got 'NA'
## Warning: Expecting numeric in N461 / R461C14: got 'NA'
## Warning: Expecting numeric in O461 / R461C15: got 'NA'
## Warning: Expecting numeric in R461 / R461C18: got 'NA'
## Warning: Expecting numeric in S461 / R461C19: got 'NA'
## Warning: Expecting numeric in T461 / R461C20: got 'NA'
## Warning: Expecting numeric in M462 / R462C13: got 'NA'
## Warning: Expecting numeric in N462 / R462C14: got 'NA'
## Warning: Expecting numeric in O462 / R462C15: got 'NA'
## Warning: Expecting numeric in R462 / R462C18: got 'NA'
## Warning: Expecting numeric in S462 / R462C19: got 'NA'
## Warning: Expecting numeric in T462 / R462C20: got 'NA'
## Warning: Expecting numeric in M463 / R463C13: got 'NA'
## Warning: Expecting numeric in N463 / R463C14: got 'NA'
## Warning: Expecting numeric in O463 / R463C15: got 'NA'
## Warning: Expecting numeric in R463 / R463C18: got 'NA'
## Warning: Expecting numeric in S463 / R463C19: got 'NA'
## Warning: Expecting numeric in T463 / R463C20: got 'NA'
## Warning: Expecting numeric in M464 / R464C13: got 'NA'
## Warning: Expecting numeric in N464 / R464C14: got 'NA'
## Warning: Expecting numeric in O464 / R464C15: got 'NA'
## Warning: Expecting numeric in R464 / R464C18: got 'NA'
## Warning: Expecting numeric in S464 / R464C19: got 'NA'
## Warning: Expecting numeric in T464 / R464C20: got 'NA'
## Warning: Expecting numeric in M465 / R465C13: got 'NA'
## Warning: Expecting numeric in N465 / R465C14: got 'NA'
## Warning: Expecting numeric in O465 / R465C15: got 'NA'
## Warning: Expecting numeric in R465 / R465C18: got 'NA'
## Warning: Expecting numeric in S465 / R465C19: got 'NA'
## Warning: Expecting numeric in T465 / R465C20: got 'NA'
## Warning: Expecting numeric in M466 / R466C13: got 'NA'
## Warning: Expecting numeric in N466 / R466C14: got 'NA'
## Warning: Expecting numeric in O466 / R466C15: got 'NA'
## Warning: Expecting numeric in R466 / R466C18: got 'NA'
## Warning: Expecting numeric in S466 / R466C19: got 'NA'
## Warning: Expecting numeric in T466 / R466C20: got 'NA'
## Warning: Expecting numeric in M467 / R467C13: got 'NA'
## Warning: Expecting numeric in N467 / R467C14: got 'NA'
## Warning: Expecting numeric in O467 / R467C15: got 'NA'
## Warning: Expecting numeric in R467 / R467C18: got 'NA'
## Warning: Expecting numeric in S467 / R467C19: got 'NA'
## Warning: Expecting numeric in T467 / R467C20: got 'NA'
## Warning: Expecting numeric in M468 / R468C13: got 'NA'
## Warning: Expecting numeric in N468 / R468C14: got 'NA'
## Warning: Expecting numeric in O468 / R468C15: got 'NA'
## Warning: Expecting numeric in R468 / R468C18: got 'NA'
## Warning: Expecting numeric in S468 / R468C19: got 'NA'
## Warning: Expecting numeric in T468 / R468C20: got 'NA'
## Warning: Expecting numeric in M469 / R469C13: got 'NA'
## Warning: Expecting numeric in N469 / R469C14: got 'NA'
## Warning: Expecting numeric in O469 / R469C15: got 'NA'
## Warning: Expecting numeric in R469 / R469C18: got 'NA'
## Warning: Expecting numeric in S469 / R469C19: got 'NA'
## Warning: Expecting numeric in T469 / R469C20: got 'NA'
## Warning: Expecting numeric in M470 / R470C13: got 'NA'
## Warning: Expecting numeric in N470 / R470C14: got 'NA'
## Warning: Expecting numeric in O470 / R470C15: got 'NA'
## Warning: Expecting numeric in R470 / R470C18: got 'NA'
## Warning: Expecting numeric in S470 / R470C19: got 'NA'
## Warning: Expecting numeric in T470 / R470C20: got 'NA'
## Warning: Expecting numeric in M471 / R471C13: got 'NA'
## Warning: Expecting numeric in N471 / R471C14: got 'NA'
## Warning: Expecting numeric in O471 / R471C15: got 'NA'
## Warning: Expecting numeric in R471 / R471C18: got 'NA'
## Warning: Expecting numeric in S471 / R471C19: got 'NA'
## Warning: Expecting numeric in T471 / R471C20: got 'NA'
## Warning: Expecting numeric in M472 / R472C13: got 'NA'
## Warning: Expecting numeric in N472 / R472C14: got 'NA'
## Warning: Expecting numeric in O472 / R472C15: got 'NA'
## Warning: Expecting numeric in R472 / R472C18: got 'NA'
## Warning: Expecting numeric in S472 / R472C19: got 'NA'
## Warning: Expecting numeric in T472 / R472C20: got 'NA'
## Warning: Expecting numeric in M473 / R473C13: got 'NA'
## Warning: Expecting numeric in N473 / R473C14: got 'NA'
## Warning: Expecting numeric in O473 / R473C15: got 'NA'
## Warning: Expecting numeric in R473 / R473C18: got 'NA'
## Warning: Expecting numeric in S473 / R473C19: got 'NA'
## Warning: Expecting numeric in T473 / R473C20: got 'NA'
## Warning: Expecting numeric in M474 / R474C13: got 'NA'
## Warning: Expecting numeric in N474 / R474C14: got 'NA'
## Warning: Expecting numeric in O474 / R474C15: got 'NA'
## Warning: Expecting numeric in R474 / R474C18: got 'NA'
## Warning: Expecting numeric in S474 / R474C19: got 'NA'
## Warning: Expecting numeric in T474 / R474C20: got 'NA'
## Warning: Expecting numeric in M475 / R475C13: got 'NA'
## Warning: Expecting numeric in N475 / R475C14: got 'NA'
## Warning: Expecting numeric in O475 / R475C15: got 'NA'
## Warning: Expecting numeric in R475 / R475C18: got 'NA'
## Warning: Expecting numeric in S475 / R475C19: got 'NA'
## Warning: Expecting numeric in T475 / R475C20: got 'NA'
## Warning: Expecting numeric in M476 / R476C13: got 'NA'
## Warning: Expecting numeric in N476 / R476C14: got 'NA'
## Warning: Expecting numeric in O476 / R476C15: got 'NA'
## Warning: Expecting numeric in R476 / R476C18: got 'NA'
## Warning: Expecting numeric in S476 / R476C19: got 'NA'
## Warning: Expecting numeric in T476 / R476C20: got 'NA'
## Warning: Expecting numeric in M477 / R477C13: got 'NA'
## Warning: Expecting numeric in N477 / R477C14: got 'NA'
## Warning: Expecting numeric in O477 / R477C15: got 'NA'
## Warning: Expecting numeric in R477 / R477C18: got 'NA'
## Warning: Expecting numeric in S477 / R477C19: got 'NA'
## Warning: Expecting numeric in T477 / R477C20: got 'NA'
## Warning: Expecting numeric in M478 / R478C13: got 'NA'
## Warning: Expecting numeric in N478 / R478C14: got 'NA'
## Warning: Expecting numeric in O478 / R478C15: got 'NA'
## Warning: Expecting numeric in R478 / R478C18: got 'NA'
## Warning: Expecting numeric in S478 / R478C19: got 'NA'
## Warning: Expecting numeric in T478 / R478C20: got 'NA'
## Warning: Expecting numeric in M479 / R479C13: got 'NA'
## Warning: Expecting numeric in N479 / R479C14: got 'NA'
## Warning: Expecting numeric in O479 / R479C15: got 'NA'
## Warning: Expecting numeric in R479 / R479C18: got 'NA'
## Warning: Expecting numeric in S479 / R479C19: got 'NA'
## Warning: Expecting numeric in T479 / R479C20: got 'NA'
## Warning: Expecting numeric in M480 / R480C13: got 'NA'
## Warning: Expecting numeric in N480 / R480C14: got 'NA'
## Warning: Expecting numeric in O480 / R480C15: got 'NA'
## Warning: Expecting numeric in R480 / R480C18: got 'NA'
## Warning: Expecting numeric in S480 / R480C19: got 'NA'
## Warning: Expecting numeric in T480 / R480C20: got 'NA'
## Warning: Expecting numeric in M481 / R481C13: got 'NA'
## Warning: Expecting numeric in N481 / R481C14: got 'NA'
## Warning: Expecting numeric in O481 / R481C15: got 'NA'
## Warning: Expecting numeric in R481 / R481C18: got 'NA'
## Warning: Expecting numeric in S481 / R481C19: got 'NA'
## Warning: Expecting numeric in T481 / R481C20: got 'NA'
## Warning: Expecting numeric in M482 / R482C13: got 'NA'
## Warning: Expecting numeric in N482 / R482C14: got 'NA'
## Warning: Expecting numeric in O482 / R482C15: got 'NA'
## Warning: Expecting numeric in R482 / R482C18: got 'NA'
## Warning: Expecting numeric in S482 / R482C19: got 'NA'
## Warning: Expecting numeric in T482 / R482C20: got 'NA'
## Warning: Expecting numeric in M483 / R483C13: got 'NA'
## Warning: Expecting numeric in N483 / R483C14: got 'NA'
## Warning: Expecting numeric in O483 / R483C15: got 'NA'
## Warning: Expecting numeric in R483 / R483C18: got 'NA'
## Warning: Expecting numeric in S483 / R483C19: got 'NA'
## Warning: Expecting numeric in T483 / R483C20: got 'NA'
## Warning: Expecting numeric in M484 / R484C13: got 'NA'
## Warning: Expecting numeric in N484 / R484C14: got 'NA'
## Warning: Expecting numeric in O484 / R484C15: got 'NA'
## Warning: Expecting numeric in R484 / R484C18: got 'NA'
## Warning: Expecting numeric in S484 / R484C19: got 'NA'
## Warning: Expecting numeric in T484 / R484C20: got 'NA'
## Warning: Expecting numeric in M485 / R485C13: got 'NA'
## Warning: Expecting numeric in N485 / R485C14: got 'NA'
## Warning: Expecting numeric in O485 / R485C15: got 'NA'
## Warning: Expecting numeric in R485 / R485C18: got 'NA'
## Warning: Expecting numeric in S485 / R485C19: got 'NA'
## Warning: Expecting numeric in T485 / R485C20: got 'NA'
## Warning: Expecting numeric in M486 / R486C13: got 'NA'
## Warning: Expecting numeric in N486 / R486C14: got 'NA'
## Warning: Expecting numeric in O486 / R486C15: got 'NA'
## Warning: Expecting numeric in R486 / R486C18: got 'NA'
## Warning: Expecting numeric in S486 / R486C19: got 'NA'
## Warning: Expecting numeric in T486 / R486C20: got 'NA'
## Warning: Expecting numeric in M487 / R487C13: got 'NA'
## Warning: Expecting numeric in N487 / R487C14: got 'NA'
## Warning: Expecting numeric in O487 / R487C15: got 'NA'
## Warning: Expecting numeric in R487 / R487C18: got 'NA'
## Warning: Expecting numeric in S487 / R487C19: got 'NA'
## Warning: Expecting numeric in T487 / R487C20: got 'NA'
## Warning: Expecting numeric in M488 / R488C13: got 'NA'
## Warning: Expecting numeric in N488 / R488C14: got 'NA'
## Warning: Expecting numeric in O488 / R488C15: got 'NA'
## Warning: Expecting numeric in R488 / R488C18: got 'NA'
## Warning: Expecting numeric in S488 / R488C19: got 'NA'
## Warning: Expecting numeric in T488 / R488C20: got 'NA'
## Warning: Expecting numeric in M489 / R489C13: got 'NA'
## Warning: Expecting numeric in N489 / R489C14: got 'NA'
## Warning: Expecting numeric in O489 / R489C15: got 'NA'
## Warning: Expecting numeric in R489 / R489C18: got 'NA'
## Warning: Expecting numeric in S489 / R489C19: got 'NA'
## Warning: Expecting numeric in T489 / R489C20: got 'NA'
## Warning: Expecting numeric in M490 / R490C13: got 'NA'
## Warning: Expecting numeric in N490 / R490C14: got 'NA'
## Warning: Expecting numeric in O490 / R490C15: got 'NA'
## Warning: Expecting numeric in R490 / R490C18: got 'NA'
## Warning: Expecting numeric in S490 / R490C19: got 'NA'
## Warning: Expecting numeric in T490 / R490C20: got 'NA'
## Warning: Expecting numeric in M491 / R491C13: got 'NA'
## Warning: Expecting numeric in N491 / R491C14: got 'NA'
## Warning: Expecting numeric in O491 / R491C15: got 'NA'
## Warning: Expecting numeric in R491 / R491C18: got 'NA'
## Warning: Expecting numeric in S491 / R491C19: got 'NA'
## Warning: Expecting numeric in T491 / R491C20: got 'NA'
## Warning: Expecting numeric in M492 / R492C13: got 'NA'
## Warning: Expecting numeric in N492 / R492C14: got 'NA'
## Warning: Expecting numeric in O492 / R492C15: got 'NA'
## Warning: Expecting numeric in R492 / R492C18: got 'NA'
## Warning: Expecting numeric in S492 / R492C19: got 'NA'
## Warning: Expecting numeric in T492 / R492C20: got 'NA'
## Warning: Expecting numeric in M493 / R493C13: got 'NA'
## Warning: Expecting numeric in N493 / R493C14: got 'NA'
## Warning: Expecting numeric in O493 / R493C15: got 'NA'
## Warning: Expecting numeric in R493 / R493C18: got 'NA'
## Warning: Expecting numeric in S493 / R493C19: got 'NA'
## Warning: Expecting numeric in T493 / R493C20: got 'NA'
## Warning: Expecting numeric in M494 / R494C13: got 'NA'
## Warning: Expecting numeric in N494 / R494C14: got 'NA'
## Warning: Expecting numeric in O494 / R494C15: got 'NA'
## Warning: Expecting numeric in R494 / R494C18: got 'NA'
## Warning: Expecting numeric in S494 / R494C19: got 'NA'
## Warning: Expecting numeric in T494 / R494C20: got 'NA'
## Warning: Expecting numeric in M495 / R495C13: got 'NA'
## Warning: Expecting numeric in N495 / R495C14: got 'NA'
## Warning: Expecting numeric in O495 / R495C15: got 'NA'
## Warning: Expecting numeric in R495 / R495C18: got 'NA'
## Warning: Expecting numeric in S495 / R495C19: got 'NA'
## Warning: Expecting numeric in T495 / R495C20: got 'NA'
## Warning: Expecting numeric in M496 / R496C13: got 'NA'
## Warning: Expecting numeric in N496 / R496C14: got 'NA'
## Warning: Expecting numeric in O496 / R496C15: got 'NA'
## Warning: Expecting numeric in R496 / R496C18: got 'NA'
## Warning: Expecting numeric in S496 / R496C19: got 'NA'
## Warning: Expecting numeric in T496 / R496C20: got 'NA'
## Warning: Expecting numeric in M497 / R497C13: got 'NA'
## Warning: Expecting numeric in N497 / R497C14: got 'NA'
## Warning: Expecting numeric in O497 / R497C15: got 'NA'
## Warning: Expecting numeric in R497 / R497C18: got 'NA'
## Warning: Expecting numeric in S497 / R497C19: got 'NA'
## Warning: Expecting numeric in T497 / R497C20: got 'NA'
## Warning: Expecting numeric in M498 / R498C13: got 'NA'
## Warning: Expecting numeric in N498 / R498C14: got 'NA'
## Warning: Expecting numeric in O498 / R498C15: got 'NA'
## Warning: Expecting numeric in R498 / R498C18: got 'NA'
## Warning: Expecting numeric in S498 / R498C19: got 'NA'
## Warning: Expecting numeric in T498 / R498C20: got 'NA'
## Warning: Expecting numeric in M499 / R499C13: got 'NA'
## Warning: Expecting numeric in N499 / R499C14: got 'NA'
## Warning: Expecting numeric in O499 / R499C15: got 'NA'
## Warning: Expecting numeric in R499 / R499C18: got 'NA'
## Warning: Expecting numeric in S499 / R499C19: got 'NA'
## Warning: Expecting numeric in T499 / R499C20: got 'NA'
## Warning: Expecting numeric in M500 / R500C13: got 'NA'
## Warning: Expecting numeric in N500 / R500C14: got 'NA'
## Warning: Expecting numeric in O500 / R500C15: got 'NA'
## Warning: Expecting numeric in R500 / R500C18: got 'NA'
## Warning: Expecting numeric in S500 / R500C19: got 'NA'
## Warning: Expecting numeric in T500 / R500C20: got 'NA'
## Warning: Expecting numeric in M501 / R501C13: got 'NA'
## Warning: Expecting numeric in N501 / R501C14: got 'NA'
## Warning: Expecting numeric in O501 / R501C15: got 'NA'
## Warning: Expecting numeric in R501 / R501C18: got 'NA'
## Warning: Expecting numeric in S501 / R501C19: got 'NA'
## Warning: Expecting numeric in T501 / R501C20: got 'NA'
## Warning: Expecting numeric in M502 / R502C13: got 'NA'
## Warning: Expecting numeric in N502 / R502C14: got 'NA'
## Warning: Expecting numeric in O502 / R502C15: got 'NA'
## Warning: Expecting numeric in R502 / R502C18: got 'NA'
## Warning: Expecting numeric in S502 / R502C19: got 'NA'
## Warning: Expecting numeric in T502 / R502C20: got 'NA'
## Warning: Expecting numeric in M503 / R503C13: got 'NA'
## Warning: Expecting numeric in N503 / R503C14: got 'NA'
## Warning: Expecting numeric in O503 / R503C15: got 'NA'
## Warning: Expecting numeric in R503 / R503C18: got 'NA'
## Warning: Expecting numeric in S503 / R503C19: got 'NA'
## Warning: Expecting numeric in T503 / R503C20: got 'NA'
## Warning: Expecting numeric in M504 / R504C13: got 'NA'
## Warning: Expecting numeric in N504 / R504C14: got 'NA'
## Warning: Expecting numeric in O504 / R504C15: got 'NA'
## Warning: Expecting numeric in R504 / R504C18: got 'NA'
## Warning: Expecting numeric in S504 / R504C19: got 'NA'
## Warning: Expecting numeric in T504 / R504C20: got 'NA'
## Warning: Expecting numeric in M505 / R505C13: got 'NA'
## Warning: Expecting numeric in N505 / R505C14: got 'NA'
## Warning: Expecting numeric in O505 / R505C15: got 'NA'
## Warning: Expecting numeric in R505 / R505C18: got 'NA'
## Warning: Expecting numeric in S505 / R505C19: got 'NA'
## Warning: Expecting numeric in T505 / R505C20: got 'NA'
## Warning: Expecting numeric in M506 / R506C13: got 'NA'
## Warning: Expecting numeric in N506 / R506C14: got 'NA'
## Warning: Expecting numeric in O506 / R506C15: got 'NA'
## Warning: Expecting numeric in R506 / R506C18: got 'NA'
## Warning: Expecting numeric in S506 / R506C19: got 'NA'
## Warning: Expecting numeric in T506 / R506C20: got 'NA'
## Warning: Expecting numeric in M507 / R507C13: got 'NA'
## Warning: Expecting numeric in N507 / R507C14: got 'NA'
## Warning: Expecting numeric in O507 / R507C15: got 'NA'
## Warning: Expecting numeric in R507 / R507C18: got 'NA'
## Warning: Expecting numeric in S507 / R507C19: got 'NA'
## Warning: Expecting numeric in T507 / R507C20: got 'NA'
## Warning: Expecting numeric in M508 / R508C13: got 'NA'
## Warning: Expecting numeric in N508 / R508C14: got 'NA'
## Warning: Expecting numeric in O508 / R508C15: got 'NA'
## Warning: Expecting numeric in R508 / R508C18: got 'NA'
## Warning: Expecting numeric in S508 / R508C19: got 'NA'
## Warning: Expecting numeric in T508 / R508C20: got 'NA'
## Warning: Expecting numeric in M509 / R509C13: got 'NA'
## Warning: Expecting numeric in N509 / R509C14: got 'NA'
## Warning: Expecting numeric in O509 / R509C15: got 'NA'
## Warning: Expecting numeric in R509 / R509C18: got 'NA'
## Warning: Expecting numeric in S509 / R509C19: got 'NA'
## Warning: Expecting numeric in T509 / R509C20: got 'NA'
## Warning: Expecting numeric in M510 / R510C13: got 'NA'
## Warning: Expecting numeric in N510 / R510C14: got 'NA'
## Warning: Expecting numeric in O510 / R510C15: got 'NA'
## Warning: Expecting numeric in R510 / R510C18: got 'NA'
## Warning: Expecting numeric in S510 / R510C19: got 'NA'
## Warning: Expecting numeric in T510 / R510C20: got 'NA'
## Warning: Expecting numeric in M511 / R511C13: got 'NA'
## Warning: Expecting numeric in N511 / R511C14: got 'NA'
## Warning: Expecting numeric in O511 / R511C15: got 'NA'
## Warning: Expecting numeric in R511 / R511C18: got 'NA'
## Warning: Expecting numeric in S511 / R511C19: got 'NA'
## Warning: Expecting numeric in T511 / R511C20: got 'NA'
## Warning: Expecting numeric in M512 / R512C13: got 'NA'
## Warning: Expecting numeric in N512 / R512C14: got 'NA'
## Warning: Expecting numeric in O512 / R512C15: got 'NA'
## Warning: Expecting numeric in R512 / R512C18: got 'NA'
## Warning: Expecting numeric in S512 / R512C19: got 'NA'
## Warning: Expecting numeric in T512 / R512C20: got 'NA'
## Warning: Expecting numeric in M513 / R513C13: got 'NA'
## Warning: Expecting numeric in N513 / R513C14: got 'NA'
## Warning: Expecting numeric in O513 / R513C15: got 'NA'
## Warning: Expecting numeric in R513 / R513C18: got 'NA'
## Warning: Expecting numeric in S513 / R513C19: got 'NA'
## Warning: Expecting numeric in T513 / R513C20: got 'NA'
## Warning: Expecting numeric in M514 / R514C13: got 'NA'
## Warning: Expecting numeric in N514 / R514C14: got 'NA'
## Warning: Expecting numeric in O514 / R514C15: got 'NA'
## Warning: Expecting numeric in R514 / R514C18: got 'NA'
## Warning: Expecting numeric in S514 / R514C19: got 'NA'
## Warning: Expecting numeric in T514 / R514C20: got 'NA'
## Warning: Expecting numeric in M515 / R515C13: got 'NA'
## Warning: Expecting numeric in N515 / R515C14: got 'NA'
## Warning: Expecting numeric in O515 / R515C15: got 'NA'
## Warning: Expecting numeric in R515 / R515C18: got 'NA'
## Warning: Expecting numeric in S515 / R515C19: got 'NA'
## Warning: Expecting numeric in T515 / R515C20: got 'NA'
## Warning: Expecting numeric in M516 / R516C13: got 'NA'
## Warning: Expecting numeric in N516 / R516C14: got 'NA'
## Warning: Expecting numeric in O516 / R516C15: got 'NA'
## Warning: Expecting numeric in R516 / R516C18: got 'NA'
## Warning: Expecting numeric in S516 / R516C19: got 'NA'
## Warning: Expecting numeric in T516 / R516C20: got 'NA'
## Warning: Expecting numeric in M517 / R517C13: got 'NA'
## Warning: Expecting numeric in N517 / R517C14: got 'NA'
## Warning: Expecting numeric in O517 / R517C15: got 'NA'
## Warning: Expecting numeric in R517 / R517C18: got 'NA'
## Warning: Expecting numeric in S517 / R517C19: got 'NA'
## Warning: Expecting numeric in T517 / R517C20: got 'NA'
## Warning: Expecting numeric in M518 / R518C13: got 'NA'
## Warning: Expecting numeric in N518 / R518C14: got 'NA'
## Warning: Expecting numeric in O518 / R518C15: got 'NA'
## Warning: Expecting numeric in R518 / R518C18: got 'NA'
## Warning: Expecting numeric in S518 / R518C19: got 'NA'
## Warning: Expecting numeric in T518 / R518C20: got 'NA'
## Warning: Expecting numeric in M519 / R519C13: got 'NA'
## Warning: Expecting numeric in N519 / R519C14: got 'NA'
## Warning: Expecting numeric in O519 / R519C15: got 'NA'
## Warning: Expecting numeric in R519 / R519C18: got 'NA'
## Warning: Expecting numeric in S519 / R519C19: got 'NA'
## Warning: Expecting numeric in T519 / R519C20: got 'NA'
## Warning: Expecting numeric in M520 / R520C13: got 'NA'
## Warning: Expecting numeric in N520 / R520C14: got 'NA'
## Warning: Expecting numeric in O520 / R520C15: got 'NA'
## Warning: Expecting numeric in R520 / R520C18: got 'NA'
## Warning: Expecting numeric in S520 / R520C19: got 'NA'
## Warning: Expecting numeric in T520 / R520C20: got 'NA'
## Warning: Expecting numeric in M521 / R521C13: got 'NA'
## Warning: Expecting numeric in N521 / R521C14: got 'NA'
## Warning: Expecting numeric in O521 / R521C15: got 'NA'
## Warning: Expecting numeric in R521 / R521C18: got 'NA'
## Warning: Expecting numeric in S521 / R521C19: got 'NA'
## Warning: Expecting numeric in T521 / R521C20: got 'NA'
## Warning: Expecting numeric in M522 / R522C13: got 'NA'
## Warning: Expecting numeric in N522 / R522C14: got 'NA'
## Warning: Expecting numeric in O522 / R522C15: got 'NA'
## Warning: Expecting numeric in R522 / R522C18: got 'NA'
## Warning: Expecting numeric in S522 / R522C19: got 'NA'
## Warning: Expecting numeric in T522 / R522C20: got 'NA'
## Warning: Expecting numeric in M523 / R523C13: got 'NA'
## Warning: Expecting numeric in N523 / R523C14: got 'NA'
## Warning: Expecting numeric in O523 / R523C15: got 'NA'
## Warning: Expecting numeric in R523 / R523C18: got 'NA'
## Warning: Expecting numeric in S523 / R523C19: got 'NA'
## Warning: Expecting numeric in T523 / R523C20: got 'NA'
## Warning: Expecting numeric in M524 / R524C13: got 'NA'
## Warning: Expecting numeric in N524 / R524C14: got 'NA'
## Warning: Expecting numeric in O524 / R524C15: got 'NA'
## Warning: Expecting numeric in R524 / R524C18: got 'NA'
## Warning: Expecting numeric in S524 / R524C19: got 'NA'
## Warning: Expecting numeric in T524 / R524C20: got 'NA'
## Warning: Expecting numeric in M525 / R525C13: got 'NA'
## Warning: Expecting numeric in N525 / R525C14: got 'NA'
## Warning: Expecting numeric in O525 / R525C15: got 'NA'
## Warning: Expecting numeric in R525 / R525C18: got 'NA'
## Warning: Expecting numeric in S525 / R525C19: got 'NA'
## Warning: Expecting numeric in T525 / R525C20: got 'NA'
## Warning: Expecting numeric in M526 / R526C13: got 'NA'
## Warning: Expecting numeric in N526 / R526C14: got 'NA'
## Warning: Expecting numeric in O526 / R526C15: got 'NA'
## Warning: Expecting numeric in R526 / R526C18: got 'NA'
## Warning: Expecting numeric in S526 / R526C19: got 'NA'
## Warning: Expecting numeric in T526 / R526C20: got 'NA'
## Warning: Expecting numeric in M527 / R527C13: got 'NA'
## Warning: Expecting numeric in N527 / R527C14: got 'NA'
## Warning: Expecting numeric in O527 / R527C15: got 'NA'
## Warning: Expecting numeric in R527 / R527C18: got 'NA'
## Warning: Expecting numeric in S527 / R527C19: got 'NA'
## Warning: Expecting numeric in T527 / R527C20: got 'NA'
## Warning: Expecting numeric in M528 / R528C13: got 'NA'
## Warning: Expecting numeric in N528 / R528C14: got 'NA'
## Warning: Expecting numeric in O528 / R528C15: got 'NA'
## Warning: Expecting numeric in R528 / R528C18: got 'NA'
## Warning: Expecting numeric in S528 / R528C19: got 'NA'
## Warning: Expecting numeric in T528 / R528C20: got 'NA'
## Warning: Expecting numeric in M529 / R529C13: got 'NA'
## Warning: Expecting numeric in N529 / R529C14: got 'NA'
## Warning: Expecting numeric in O529 / R529C15: got 'NA'
## Warning: Expecting numeric in R529 / R529C18: got 'NA'
## Warning: Expecting numeric in S529 / R529C19: got 'NA'
## Warning: Expecting numeric in T529 / R529C20: got 'NA'
## Warning: Expecting numeric in M530 / R530C13: got 'NA'
## Warning: Expecting numeric in N530 / R530C14: got 'NA'
## Warning: Expecting numeric in O530 / R530C15: got 'NA'
## Warning: Expecting numeric in R530 / R530C18: got 'NA'
## Warning: Expecting numeric in S530 / R530C19: got 'NA'
## Warning: Expecting numeric in T530 / R530C20: got 'NA'
## Warning: Expecting numeric in M531 / R531C13: got 'NA'
## Warning: Expecting numeric in N531 / R531C14: got 'NA'
## Warning: Expecting numeric in O531 / R531C15: got 'NA'
## Warning: Expecting numeric in R531 / R531C18: got 'NA'
## Warning: Expecting numeric in S531 / R531C19: got 'NA'
## Warning: Expecting numeric in T531 / R531C20: got 'NA'
## Warning: Expecting numeric in M532 / R532C13: got 'NA'
## Warning: Expecting numeric in N532 / R532C14: got 'NA'
## Warning: Expecting numeric in O532 / R532C15: got 'NA'
## Warning: Expecting numeric in R532 / R532C18: got 'NA'
## Warning: Expecting numeric in S532 / R532C19: got 'NA'
## Warning: Expecting numeric in T532 / R532C20: got 'NA'
## Warning: Expecting numeric in M533 / R533C13: got 'NA'
## Warning: Expecting numeric in N533 / R533C14: got 'NA'
## Warning: Expecting numeric in O533 / R533C15: got 'NA'
## Warning: Expecting numeric in R533 / R533C18: got 'NA'
## Warning: Expecting numeric in S533 / R533C19: got 'NA'
## Warning: Expecting numeric in T533 / R533C20: got 'NA'
## Warning: Expecting numeric in M534 / R534C13: got 'NA'
## Warning: Expecting numeric in N534 / R534C14: got 'NA'
## Warning: Expecting numeric in O534 / R534C15: got 'NA'
## Warning: Expecting numeric in R534 / R534C18: got 'NA'
## Warning: Expecting numeric in S534 / R534C19: got 'NA'
## Warning: Expecting numeric in T534 / R534C20: got 'NA'
## Warning: Expecting numeric in M535 / R535C13: got 'NA'
## Warning: Expecting numeric in N535 / R535C14: got 'NA'
## Warning: Expecting numeric in O535 / R535C15: got 'NA'
## Warning: Expecting numeric in R535 / R535C18: got 'NA'
## Warning: Expecting numeric in S535 / R535C19: got 'NA'
## Warning: Expecting numeric in T535 / R535C20: got 'NA'
## Warning: Expecting numeric in M536 / R536C13: got 'NA'
## Warning: Expecting numeric in N536 / R536C14: got 'NA'
## Warning: Expecting numeric in O536 / R536C15: got 'NA'
## Warning: Expecting numeric in R536 / R536C18: got 'NA'
## Warning: Expecting numeric in S536 / R536C19: got 'NA'
## Warning: Expecting numeric in T536 / R536C20: got 'NA'
## Warning: Expecting numeric in M537 / R537C13: got 'NA'
## Warning: Expecting numeric in N537 / R537C14: got 'NA'
## Warning: Expecting numeric in O537 / R537C15: got 'NA'
## Warning: Expecting numeric in R537 / R537C18: got 'NA'
## Warning: Expecting numeric in S537 / R537C19: got 'NA'
## Warning: Expecting numeric in T537 / R537C20: got 'NA'
## Warning: Expecting numeric in M538 / R538C13: got 'NA'
## Warning: Expecting numeric in N538 / R538C14: got 'NA'
## Warning: Expecting numeric in O538 / R538C15: got 'NA'
## Warning: Expecting numeric in R538 / R538C18: got 'NA'
## Warning: Expecting numeric in S538 / R538C19: got 'NA'
## Warning: Expecting numeric in T538 / R538C20: got 'NA'
## Warning: Expecting numeric in M539 / R539C13: got 'NA'
## Warning: Expecting numeric in N539 / R539C14: got 'NA'
## Warning: Expecting numeric in O539 / R539C15: got 'NA'
## Warning: Expecting numeric in R539 / R539C18: got 'NA'
## Warning: Expecting numeric in S539 / R539C19: got 'NA'
## Warning: Expecting numeric in T539 / R539C20: got 'NA'
## Warning: Expecting numeric in M540 / R540C13: got 'NA'
## Warning: Expecting numeric in N540 / R540C14: got 'NA'
## Warning: Expecting numeric in O540 / R540C15: got 'NA'
## Warning: Expecting numeric in R540 / R540C18: got 'NA'
## Warning: Expecting numeric in S540 / R540C19: got 'NA'
## Warning: Expecting numeric in T540 / R540C20: got 'NA'
## Warning: Expecting numeric in M541 / R541C13: got 'NA'
## Warning: Expecting numeric in N541 / R541C14: got 'NA'
## Warning: Expecting numeric in O541 / R541C15: got 'NA'
## Warning: Expecting numeric in R541 / R541C18: got 'NA'
## Warning: Expecting numeric in S541 / R541C19: got 'NA'
## Warning: Expecting numeric in T541 / R541C20: got 'NA'
## Warning: Expecting numeric in M542 / R542C13: got 'NA'
## Warning: Expecting numeric in N542 / R542C14: got 'NA'
## Warning: Expecting numeric in O542 / R542C15: got 'NA'
## Warning: Expecting numeric in R542 / R542C18: got 'NA'
## Warning: Expecting numeric in S542 / R542C19: got 'NA'
## Warning: Expecting numeric in T542 / R542C20: got 'NA'
## Warning: Expecting numeric in M543 / R543C13: got 'NA'
## Warning: Expecting numeric in N543 / R543C14: got 'NA'
## Warning: Expecting numeric in O543 / R543C15: got 'NA'
## Warning: Expecting numeric in R543 / R543C18: got 'NA'
## Warning: Expecting numeric in S543 / R543C19: got 'NA'
## Warning: Expecting numeric in T543 / R543C20: got 'NA'
## Warning: Expecting numeric in M544 / R544C13: got 'NA'
## Warning: Expecting numeric in N544 / R544C14: got 'NA'
## Warning: Expecting numeric in O544 / R544C15: got 'NA'
## Warning: Expecting numeric in R544 / R544C18: got 'NA'
## Warning: Expecting numeric in S544 / R544C19: got 'NA'
## Warning: Expecting numeric in T544 / R544C20: got 'NA'
## Warning: Expecting numeric in M545 / R545C13: got 'NA'
## Warning: Expecting numeric in N545 / R545C14: got 'NA'
## Warning: Expecting numeric in O545 / R545C15: got 'NA'
## Warning: Expecting numeric in R545 / R545C18: got 'NA'
## Warning: Expecting numeric in S545 / R545C19: got 'NA'
## Warning: Expecting numeric in T545 / R545C20: got 'NA'
## Warning: Expecting numeric in M546 / R546C13: got 'NA'
## Warning: Expecting numeric in N546 / R546C14: got 'NA'
## Warning: Expecting numeric in O546 / R546C15: got 'NA'
## Warning: Expecting numeric in R546 / R546C18: got 'NA'
## Warning: Expecting numeric in S546 / R546C19: got 'NA'
## Warning: Expecting numeric in T546 / R546C20: got 'NA'
## Warning: Expecting numeric in M547 / R547C13: got 'NA'
## Warning: Expecting numeric in N547 / R547C14: got 'NA'
## Warning: Expecting numeric in O547 / R547C15: got 'NA'
## Warning: Expecting numeric in R547 / R547C18: got 'NA'
## Warning: Expecting numeric in S547 / R547C19: got 'NA'
## Warning: Expecting numeric in T547 / R547C20: got 'NA'
## Warning: Expecting numeric in M548 / R548C13: got 'NA'
## Warning: Expecting numeric in N548 / R548C14: got 'NA'
## Warning: Expecting numeric in O548 / R548C15: got 'NA'
## Warning: Expecting numeric in R548 / R548C18: got 'NA'
## Warning: Expecting numeric in S548 / R548C19: got 'NA'
## Warning: Expecting numeric in T548 / R548C20: got 'NA'
## Warning: Expecting numeric in M549 / R549C13: got 'NA'
## Warning: Expecting numeric in N549 / R549C14: got 'NA'
## Warning: Expecting numeric in O549 / R549C15: got 'NA'
## Warning: Expecting numeric in R549 / R549C18: got 'NA'
## Warning: Expecting numeric in S549 / R549C19: got 'NA'
## Warning: Expecting numeric in T549 / R549C20: got 'NA'
## Warning: Expecting numeric in M550 / R550C13: got 'NA'
## Warning: Expecting numeric in N550 / R550C14: got 'NA'
## Warning: Expecting numeric in O550 / R550C15: got 'NA'
## Warning: Expecting numeric in R550 / R550C18: got 'NA'
## Warning: Expecting numeric in S550 / R550C19: got 'NA'
## Warning: Expecting numeric in T550 / R550C20: got 'NA'
## Warning: Expecting numeric in M551 / R551C13: got 'NA'
## Warning: Expecting numeric in N551 / R551C14: got 'NA'
## Warning: Expecting numeric in O551 / R551C15: got 'NA'
## Warning: Expecting numeric in R551 / R551C18: got 'NA'
## Warning: Expecting numeric in S551 / R551C19: got 'NA'
## Warning: Expecting numeric in T551 / R551C20: got 'NA'
## Warning: Expecting numeric in M552 / R552C13: got 'NA'
## Warning: Expecting numeric in N552 / R552C14: got 'NA'
## Warning: Expecting numeric in O552 / R552C15: got 'NA'
## Warning: Expecting numeric in R552 / R552C18: got 'NA'
## Warning: Expecting numeric in S552 / R552C19: got 'NA'
## Warning: Expecting numeric in T552 / R552C20: got 'NA'
## Warning: Expecting numeric in M553 / R553C13: got 'NA'
## Warning: Expecting numeric in N553 / R553C14: got 'NA'
## Warning: Expecting numeric in O553 / R553C15: got 'NA'
## Warning: Expecting numeric in R553 / R553C18: got 'NA'
## Warning: Expecting numeric in S553 / R553C19: got 'NA'
## Warning: Expecting numeric in T553 / R553C20: got 'NA'
## Warning: Expecting numeric in M554 / R554C13: got 'NA'
## Warning: Expecting numeric in N554 / R554C14: got 'NA'
## Warning: Expecting numeric in O554 / R554C15: got 'NA'
## Warning: Expecting numeric in R554 / R554C18: got 'NA'
## Warning: Expecting numeric in S554 / R554C19: got 'NA'
## Warning: Expecting numeric in T554 / R554C20: got 'NA'
## Warning: Expecting numeric in M555 / R555C13: got 'NA'
## Warning: Expecting numeric in N555 / R555C14: got 'NA'
## Warning: Expecting numeric in O555 / R555C15: got 'NA'
## Warning: Expecting numeric in R555 / R555C18: got 'NA'
## Warning: Expecting numeric in S555 / R555C19: got 'NA'
## Warning: Expecting numeric in T555 / R555C20: got 'NA'
## Warning: Expecting numeric in M556 / R556C13: got 'NA'
## Warning: Expecting numeric in N556 / R556C14: got 'NA'
## Warning: Expecting numeric in O556 / R556C15: got 'NA'
## Warning: Expecting numeric in R556 / R556C18: got 'NA'
## Warning: Expecting numeric in S556 / R556C19: got 'NA'
## Warning: Expecting numeric in T556 / R556C20: got 'NA'
## Warning: Expecting numeric in M557 / R557C13: got 'NA'
## Warning: Expecting numeric in N557 / R557C14: got 'NA'
## Warning: Expecting numeric in O557 / R557C15: got 'NA'
## Warning: Expecting numeric in R557 / R557C18: got 'NA'
## Warning: Expecting numeric in S557 / R557C19: got 'NA'
## Warning: Expecting numeric in T557 / R557C20: got 'NA'
## Warning: Expecting numeric in M558 / R558C13: got 'NA'
## Warning: Expecting numeric in N558 / R558C14: got 'NA'
## Warning: Expecting numeric in O558 / R558C15: got 'NA'
## Warning: Expecting numeric in R558 / R558C18: got 'NA'
## Warning: Expecting numeric in S558 / R558C19: got 'NA'
## Warning: Expecting numeric in T558 / R558C20: got 'NA'
## Warning: Expecting numeric in M559 / R559C13: got 'NA'
## Warning: Expecting numeric in N559 / R559C14: got 'NA'
## Warning: Expecting numeric in O559 / R559C15: got 'NA'
## Warning: Expecting numeric in R559 / R559C18: got 'NA'
## Warning: Expecting numeric in S559 / R559C19: got 'NA'
## Warning: Expecting numeric in T559 / R559C20: got 'NA'
## Warning: Expecting numeric in M560 / R560C13: got 'NA'
## Warning: Expecting numeric in N560 / R560C14: got 'NA'
## Warning: Expecting numeric in O560 / R560C15: got 'NA'
## Warning: Expecting numeric in R560 / R560C18: got 'NA'
## Warning: Expecting numeric in S560 / R560C19: got 'NA'
## Warning: Expecting numeric in T560 / R560C20: got 'NA'
## Warning: Expecting numeric in M561 / R561C13: got 'NA'
## Warning: Expecting numeric in N561 / R561C14: got 'NA'
## Warning: Expecting numeric in O561 / R561C15: got 'NA'
## Warning: Expecting numeric in R561 / R561C18: got 'NA'
## Warning: Expecting numeric in S561 / R561C19: got 'NA'
## Warning: Expecting numeric in T561 / R561C20: got 'NA'
## Warning: Expecting numeric in M562 / R562C13: got 'NA'
## Warning: Expecting numeric in N562 / R562C14: got 'NA'
## Warning: Expecting numeric in O562 / R562C15: got 'NA'
## Warning: Expecting numeric in R562 / R562C18: got 'NA'
## Warning: Expecting numeric in S562 / R562C19: got 'NA'
## Warning: Expecting numeric in T562 / R562C20: got 'NA'
## Warning: Expecting numeric in M563 / R563C13: got 'NA'
## Warning: Expecting numeric in N563 / R563C14: got 'NA'
## Warning: Expecting numeric in O563 / R563C15: got 'NA'
## Warning: Expecting numeric in R563 / R563C18: got 'NA'
## Warning: Expecting numeric in S563 / R563C19: got 'NA'
## Warning: Expecting numeric in T563 / R563C20: got 'NA'
## Warning: Expecting numeric in M564 / R564C13: got 'NA'
## Warning: Expecting numeric in N564 / R564C14: got 'NA'
## Warning: Expecting numeric in O564 / R564C15: got 'NA'
## Warning: Expecting numeric in R564 / R564C18: got 'NA'
## Warning: Expecting numeric in S564 / R564C19: got 'NA'
## Warning: Expecting numeric in T564 / R564C20: got 'NA'
## Warning: Expecting numeric in M565 / R565C13: got 'NA'
## Warning: Expecting numeric in N565 / R565C14: got 'NA'
## Warning: Expecting numeric in O565 / R565C15: got 'NA'
## Warning: Expecting numeric in R565 / R565C18: got 'NA'
## Warning: Expecting numeric in S565 / R565C19: got 'NA'
## Warning: Expecting numeric in T565 / R565C20: got 'NA'
## Warning: Expecting numeric in M566 / R566C13: got 'NA'
## Warning: Expecting numeric in N566 / R566C14: got 'NA'
## Warning: Expecting numeric in O566 / R566C15: got 'NA'
## Warning: Expecting numeric in R566 / R566C18: got 'NA'
## Warning: Expecting numeric in S566 / R566C19: got 'NA'
## Warning: Expecting numeric in T566 / R566C20: got 'NA'
## Warning: Expecting numeric in M567 / R567C13: got 'NA'
## Warning: Expecting numeric in N567 / R567C14: got 'NA'
## Warning: Expecting numeric in O567 / R567C15: got 'NA'
## Warning: Expecting numeric in R567 / R567C18: got 'NA'
## Warning: Expecting numeric in S567 / R567C19: got 'NA'
## Warning: Expecting numeric in T567 / R567C20: got 'NA'
## Warning: Expecting numeric in M568 / R568C13: got 'NA'
## Warning: Expecting numeric in N568 / R568C14: got 'NA'
## Warning: Expecting numeric in O568 / R568C15: got 'NA'
## Warning: Expecting numeric in R568 / R568C18: got 'NA'
## Warning: Expecting numeric in S568 / R568C19: got 'NA'
## Warning: Expecting numeric in T568 / R568C20: got 'NA'
## Warning: Expecting numeric in M569 / R569C13: got 'NA'
## Warning: Expecting numeric in N569 / R569C14: got 'NA'
## Warning: Expecting numeric in O569 / R569C15: got 'NA'
## Warning: Expecting numeric in R569 / R569C18: got 'NA'
## Warning: Expecting numeric in S569 / R569C19: got 'NA'
## Warning: Expecting numeric in T569 / R569C20: got 'NA'
## Warning: Expecting numeric in M570 / R570C13: got 'NA'
## Warning: Expecting numeric in N570 / R570C14: got 'NA'
## Warning: Expecting numeric in O570 / R570C15: got 'NA'
## Warning: Expecting numeric in R570 / R570C18: got 'NA'
## Warning: Expecting numeric in S570 / R570C19: got 'NA'
## Warning: Expecting numeric in T570 / R570C20: got 'NA'
## Warning: Expecting numeric in M571 / R571C13: got 'NA'
## Warning: Expecting numeric in N571 / R571C14: got 'NA'
## Warning: Expecting numeric in O571 / R571C15: got 'NA'
## Warning: Expecting numeric in R571 / R571C18: got 'NA'
## Warning: Expecting numeric in S571 / R571C19: got 'NA'
## Warning: Expecting numeric in T571 / R571C20: got 'NA'
## Warning: Expecting numeric in M572 / R572C13: got 'NA'
## Warning: Expecting numeric in N572 / R572C14: got 'NA'
## Warning: Expecting numeric in O572 / R572C15: got 'NA'
## Warning: Expecting numeric in R572 / R572C18: got 'NA'
## Warning: Expecting numeric in S572 / R572C19: got 'NA'
## Warning: Expecting numeric in T572 / R572C20: got 'NA'
## Warning: Expecting numeric in M573 / R573C13: got 'NA'
## Warning: Expecting numeric in N573 / R573C14: got 'NA'
## Warning: Expecting numeric in O573 / R573C15: got 'NA'
## Warning: Expecting numeric in R573 / R573C18: got 'NA'
## Warning: Expecting numeric in S573 / R573C19: got 'NA'
## Warning: Expecting numeric in T573 / R573C20: got 'NA'
## Warning: Expecting numeric in M574 / R574C13: got 'NA'
## Warning: Expecting numeric in N574 / R574C14: got 'NA'
## Warning: Expecting numeric in O574 / R574C15: got 'NA'
## Warning: Expecting numeric in R574 / R574C18: got 'NA'
## Warning: Expecting numeric in S574 / R574C19: got 'NA'
## Warning: Expecting numeric in T574 / R574C20: got 'NA'
## Warning: Expecting numeric in M575 / R575C13: got 'NA'
## Warning: Expecting numeric in N575 / R575C14: got 'NA'
## Warning: Expecting numeric in O575 / R575C15: got 'NA'
## Warning: Expecting numeric in R575 / R575C18: got 'NA'
## Warning: Expecting numeric in S575 / R575C19: got 'NA'
## Warning: Expecting numeric in T575 / R575C20: got 'NA'
## Warning: Expecting numeric in M576 / R576C13: got 'NA'
## Warning: Expecting numeric in N576 / R576C14: got 'NA'
## Warning: Expecting numeric in O576 / R576C15: got 'NA'
## Warning: Expecting numeric in R576 / R576C18: got 'NA'
## Warning: Expecting numeric in S576 / R576C19: got 'NA'
## Warning: Expecting numeric in T576 / R576C20: got 'NA'
## Warning: Expecting numeric in M577 / R577C13: got 'NA'
## Warning: Expecting numeric in N577 / R577C14: got 'NA'
## Warning: Expecting numeric in O577 / R577C15: got 'NA'
## Warning: Expecting numeric in R577 / R577C18: got 'NA'
## Warning: Expecting numeric in S577 / R577C19: got 'NA'
## Warning: Expecting numeric in T577 / R577C20: got 'NA'
## Warning: Expecting numeric in M578 / R578C13: got 'NA'
## Warning: Expecting numeric in N578 / R578C14: got 'NA'
## Warning: Expecting numeric in O578 / R578C15: got 'NA'
## Warning: Expecting numeric in R578 / R578C18: got 'NA'
## Warning: Expecting numeric in S578 / R578C19: got 'NA'
## Warning: Expecting numeric in T578 / R578C20: got 'NA'
## Warning: Expecting numeric in M579 / R579C13: got 'NA'
## Warning: Expecting numeric in N579 / R579C14: got 'NA'
## Warning: Expecting numeric in O579 / R579C15: got 'NA'
## Warning: Expecting numeric in R579 / R579C18: got 'NA'
## Warning: Expecting numeric in S579 / R579C19: got 'NA'
## Warning: Expecting numeric in T579 / R579C20: got 'NA'
## Warning: Expecting numeric in M580 / R580C13: got 'NA'
## Warning: Expecting numeric in N580 / R580C14: got 'NA'
## Warning: Expecting numeric in O580 / R580C15: got 'NA'
## Warning: Expecting numeric in R580 / R580C18: got 'NA'
## Warning: Expecting numeric in S580 / R580C19: got 'NA'
## Warning: Expecting numeric in T580 / R580C20: got 'NA'
## Warning: Expecting numeric in M581 / R581C13: got 'NA'
## Warning: Expecting numeric in N581 / R581C14: got 'NA'
## Warning: Expecting numeric in O581 / R581C15: got 'NA'
## Warning: Expecting numeric in R581 / R581C18: got 'NA'
## Warning: Expecting numeric in S581 / R581C19: got 'NA'
## Warning: Expecting numeric in T581 / R581C20: got 'NA'
## Warning: Expecting numeric in M582 / R582C13: got 'NA'
## Warning: Expecting numeric in N582 / R582C14: got 'NA'
## Warning: Expecting numeric in O582 / R582C15: got 'NA'
## Warning: Expecting numeric in R582 / R582C18: got 'NA'
## Warning: Expecting numeric in S582 / R582C19: got 'NA'
## Warning: Expecting numeric in T582 / R582C20: got 'NA'
## Warning: Expecting numeric in M583 / R583C13: got 'NA'
## Warning: Expecting numeric in N583 / R583C14: got 'NA'
## Warning: Expecting numeric in O583 / R583C15: got 'NA'
## Warning: Expecting numeric in R583 / R583C18: got 'NA'
## Warning: Expecting numeric in S583 / R583C19: got 'NA'
## Warning: Expecting numeric in T583 / R583C20: got 'NA'
## Warning: Expecting numeric in M584 / R584C13: got 'NA'
## Warning: Expecting numeric in N584 / R584C14: got 'NA'
## Warning: Expecting numeric in O584 / R584C15: got 'NA'
## Warning: Expecting numeric in R584 / R584C18: got 'NA'
## Warning: Expecting numeric in S584 / R584C19: got 'NA'
## Warning: Expecting numeric in T584 / R584C20: got 'NA'
## Warning: Expecting numeric in M585 / R585C13: got 'NA'
## Warning: Expecting numeric in N585 / R585C14: got 'NA'
## Warning: Expecting numeric in O585 / R585C15: got 'NA'
## Warning: Expecting numeric in R585 / R585C18: got 'NA'
## Warning: Expecting numeric in S585 / R585C19: got 'NA'
## Warning: Expecting numeric in T585 / R585C20: got 'NA'
## Warning: Expecting numeric in M586 / R586C13: got 'NA'
## Warning: Expecting numeric in N586 / R586C14: got 'NA'
## Warning: Expecting numeric in O586 / R586C15: got 'NA'
## Warning: Expecting numeric in R586 / R586C18: got 'NA'
## Warning: Expecting numeric in S586 / R586C19: got 'NA'
## Warning: Expecting numeric in T586 / R586C20: got 'NA'
## Warning: Expecting numeric in M587 / R587C13: got 'NA'
## Warning: Expecting numeric in N587 / R587C14: got 'NA'
## Warning: Expecting numeric in O587 / R587C15: got 'NA'
## Warning: Expecting numeric in R587 / R587C18: got 'NA'
## Warning: Expecting numeric in S587 / R587C19: got 'NA'
## Warning: Expecting numeric in T587 / R587C20: got 'NA'
## Warning: Expecting numeric in M588 / R588C13: got 'NA'
## Warning: Expecting numeric in N588 / R588C14: got 'NA'
## Warning: Expecting numeric in O588 / R588C15: got 'NA'
## Warning: Expecting numeric in R588 / R588C18: got 'NA'
## Warning: Expecting numeric in S588 / R588C19: got 'NA'
## Warning: Expecting numeric in T588 / R588C20: got 'NA'
## Warning: Expecting numeric in M589 / R589C13: got 'NA'
## Warning: Expecting numeric in N589 / R589C14: got 'NA'
## Warning: Expecting numeric in O589 / R589C15: got 'NA'
## Warning: Expecting numeric in R589 / R589C18: got 'NA'
## Warning: Expecting numeric in S589 / R589C19: got 'NA'
## Warning: Expecting numeric in T589 / R589C20: got 'NA'
## Warning: Expecting numeric in M590 / R590C13: got 'NA'
## Warning: Expecting numeric in N590 / R590C14: got 'NA'
## Warning: Expecting numeric in O590 / R590C15: got 'NA'
## Warning: Expecting numeric in R590 / R590C18: got 'NA'
## Warning: Expecting numeric in S590 / R590C19: got 'NA'
## Warning: Expecting numeric in T590 / R590C20: got 'NA'
## Warning: Expecting numeric in M591 / R591C13: got 'NA'
## Warning: Expecting numeric in N591 / R591C14: got 'NA'
## Warning: Expecting numeric in O591 / R591C15: got 'NA'
## Warning: Expecting numeric in R591 / R591C18: got 'NA'
## Warning: Expecting numeric in S591 / R591C19: got 'NA'
## Warning: Expecting numeric in T591 / R591C20: got 'NA'
## Warning: Expecting numeric in M592 / R592C13: got 'NA'
## Warning: Expecting numeric in N592 / R592C14: got 'NA'
## Warning: Expecting numeric in O592 / R592C15: got 'NA'
## Warning: Expecting numeric in R592 / R592C18: got 'NA'
## Warning: Expecting numeric in S592 / R592C19: got 'NA'
## Warning: Expecting numeric in T592 / R592C20: got 'NA'
## Warning: Expecting numeric in M593 / R593C13: got 'NA'
## Warning: Expecting numeric in N593 / R593C14: got 'NA'
## Warning: Expecting numeric in O593 / R593C15: got 'NA'
## Warning: Expecting numeric in R593 / R593C18: got 'NA'
## Warning: Expecting numeric in S593 / R593C19: got 'NA'
## Warning: Expecting numeric in T593 / R593C20: got 'NA'
## Warning: Expecting numeric in M594 / R594C13: got 'NA'
## Warning: Expecting numeric in N594 / R594C14: got 'NA'
## Warning: Expecting numeric in O594 / R594C15: got 'NA'
## Warning: Expecting numeric in R594 / R594C18: got 'NA'
## Warning: Expecting numeric in S594 / R594C19: got 'NA'
## Warning: Expecting numeric in T594 / R594C20: got 'NA'
## Warning: Expecting numeric in M595 / R595C13: got 'NA'
## Warning: Expecting numeric in N595 / R595C14: got 'NA'
## Warning: Expecting numeric in O595 / R595C15: got 'NA'
## Warning: Expecting numeric in R595 / R595C18: got 'NA'
## Warning: Expecting numeric in S595 / R595C19: got 'NA'
## Warning: Expecting numeric in T595 / R595C20: got 'NA'
## Warning: Expecting numeric in M596 / R596C13: got 'NA'
## Warning: Expecting numeric in N596 / R596C14: got 'NA'
## Warning: Expecting numeric in O596 / R596C15: got 'NA'
## Warning: Expecting numeric in R596 / R596C18: got 'NA'
## Warning: Expecting numeric in S596 / R596C19: got 'NA'
## Warning: Expecting numeric in T596 / R596C20: got 'NA'
## Warning: Expecting numeric in M597 / R597C13: got 'NA'
## Warning: Expecting numeric in N597 / R597C14: got 'NA'
## Warning: Expecting numeric in O597 / R597C15: got 'NA'
## Warning: Expecting numeric in R597 / R597C18: got 'NA'
## Warning: Expecting numeric in S597 / R597C19: got 'NA'
## Warning: Expecting numeric in T597 / R597C20: got 'NA'
## Warning: Expecting numeric in M598 / R598C13: got 'NA'
## Warning: Expecting numeric in N598 / R598C14: got 'NA'
## Warning: Expecting numeric in O598 / R598C15: got 'NA'
## Warning: Expecting numeric in R598 / R598C18: got 'NA'
## Warning: Expecting numeric in S598 / R598C19: got 'NA'
## Warning: Expecting numeric in T598 / R598C20: got 'NA'
## Warning: Expecting numeric in M599 / R599C13: got 'NA'
## Warning: Expecting numeric in N599 / R599C14: got 'NA'
## Warning: Expecting numeric in O599 / R599C15: got 'NA'
## Warning: Expecting numeric in R599 / R599C18: got 'NA'
## Warning: Expecting numeric in S599 / R599C19: got 'NA'
## Warning: Expecting numeric in T599 / R599C20: got 'NA'
## Warning: Expecting numeric in M600 / R600C13: got 'NA'
## Warning: Expecting numeric in N600 / R600C14: got 'NA'
## Warning: Expecting numeric in O600 / R600C15: got 'NA'
## Warning: Expecting numeric in R600 / R600C18: got 'NA'
## Warning: Expecting numeric in S600 / R600C19: got 'NA'
## Warning: Expecting numeric in T600 / R600C20: got 'NA'
## Warning: Expecting numeric in M601 / R601C13: got 'NA'
## Warning: Expecting numeric in N601 / R601C14: got 'NA'
## Warning: Expecting numeric in O601 / R601C15: got 'NA'
## Warning: Expecting numeric in R601 / R601C18: got 'NA'
## Warning: Expecting numeric in S601 / R601C19: got 'NA'
## Warning: Expecting numeric in T601 / R601C20: got 'NA'
## Warning: Expecting numeric in M602 / R602C13: got 'NA'
## Warning: Expecting numeric in N602 / R602C14: got 'NA'
## Warning: Expecting numeric in O602 / R602C15: got 'NA'
## Warning: Expecting numeric in R602 / R602C18: got 'NA'
## Warning: Expecting numeric in S602 / R602C19: got 'NA'
## Warning: Expecting numeric in T602 / R602C20: got 'NA'
## Warning: Expecting numeric in M603 / R603C13: got 'NA'
## Warning: Expecting numeric in N603 / R603C14: got 'NA'
## Warning: Expecting numeric in O603 / R603C15: got 'NA'
## Warning: Expecting numeric in R603 / R603C18: got 'NA'
## Warning: Expecting numeric in S603 / R603C19: got 'NA'
## Warning: Expecting numeric in T603 / R603C20: got 'NA'
## Warning: Expecting numeric in M604 / R604C13: got 'NA'
## Warning: Expecting numeric in N604 / R604C14: got 'NA'
## Warning: Expecting numeric in O604 / R604C15: got 'NA'
## Warning: Expecting numeric in R604 / R604C18: got 'NA'
## Warning: Expecting numeric in S604 / R604C19: got 'NA'
## Warning: Expecting numeric in T604 / R604C20: got 'NA'
## Warning: Expecting numeric in M605 / R605C13: got 'NA'
## Warning: Expecting numeric in N605 / R605C14: got 'NA'
## Warning: Expecting numeric in O605 / R605C15: got 'NA'
## Warning: Expecting numeric in R605 / R605C18: got 'NA'
## Warning: Expecting numeric in S605 / R605C19: got 'NA'
## Warning: Expecting numeric in T605 / R605C20: got 'NA'
## Warning: Expecting numeric in M606 / R606C13: got 'NA'
## Warning: Expecting numeric in N606 / R606C14: got 'NA'
## Warning: Expecting numeric in O606 / R606C15: got 'NA'
## Warning: Expecting numeric in R606 / R606C18: got 'NA'
## Warning: Expecting numeric in S606 / R606C19: got 'NA'
## Warning: Expecting numeric in T606 / R606C20: got 'NA'
## Warning: Expecting numeric in M607 / R607C13: got 'NA'
## Warning: Expecting numeric in N607 / R607C14: got 'NA'
## Warning: Expecting numeric in O607 / R607C15: got 'NA'
## Warning: Expecting numeric in R607 / R607C18: got 'NA'
## Warning: Expecting numeric in S607 / R607C19: got 'NA'
## Warning: Expecting numeric in T607 / R607C20: got 'NA'
## Warning: Expecting numeric in M608 / R608C13: got 'NA'
## Warning: Expecting numeric in N608 / R608C14: got 'NA'
## Warning: Expecting numeric in O608 / R608C15: got 'NA'
## Warning: Expecting numeric in R608 / R608C18: got 'NA'
## Warning: Expecting numeric in S608 / R608C19: got 'NA'
## Warning: Expecting numeric in T608 / R608C20: got 'NA'
## Warning: Expecting numeric in M609 / R609C13: got 'NA'
## Warning: Expecting numeric in N609 / R609C14: got 'NA'
## Warning: Expecting numeric in O609 / R609C15: got 'NA'
## Warning: Expecting numeric in R609 / R609C18: got 'NA'
## Warning: Expecting numeric in S609 / R609C19: got 'NA'
## Warning: Expecting numeric in T609 / R609C20: got 'NA'
## Warning: Expecting numeric in M610 / R610C13: got 'NA'
## Warning: Expecting numeric in N610 / R610C14: got 'NA'
## Warning: Expecting numeric in O610 / R610C15: got 'NA'
## Warning: Expecting numeric in R610 / R610C18: got 'NA'
## Warning: Expecting numeric in S610 / R610C19: got 'NA'
## Warning: Expecting numeric in T610 / R610C20: got 'NA'
## Warning: Expecting numeric in M611 / R611C13: got 'NA'
## Warning: Expecting numeric in N611 / R611C14: got 'NA'
## Warning: Expecting numeric in O611 / R611C15: got 'NA'
## Warning: Expecting numeric in R611 / R611C18: got 'NA'
## Warning: Expecting numeric in S611 / R611C19: got 'NA'
## Warning: Expecting numeric in T611 / R611C20: got 'NA'
## Warning: Expecting numeric in M612 / R612C13: got 'NA'
## Warning: Expecting numeric in N612 / R612C14: got 'NA'
## Warning: Expecting numeric in O612 / R612C15: got 'NA'
## Warning: Expecting numeric in R612 / R612C18: got 'NA'
## Warning: Expecting numeric in S612 / R612C19: got 'NA'
## Warning: Expecting numeric in T612 / R612C20: got 'NA'
## Warning: Expecting numeric in M613 / R613C13: got 'NA'
## Warning: Expecting numeric in N613 / R613C14: got 'NA'
## Warning: Expecting numeric in O613 / R613C15: got 'NA'
## Warning: Expecting numeric in R613 / R613C18: got 'NA'
## Warning: Expecting numeric in S613 / R613C19: got 'NA'
## Warning: Expecting numeric in T613 / R613C20: got 'NA'
## Warning: Expecting numeric in M614 / R614C13: got 'NA'
## Warning: Expecting numeric in N614 / R614C14: got 'NA'
## Warning: Expecting numeric in O614 / R614C15: got 'NA'
## Warning: Expecting numeric in R614 / R614C18: got 'NA'
## Warning: Expecting numeric in S614 / R614C19: got 'NA'
## Warning: Expecting numeric in T614 / R614C20: got 'NA'
## Warning: Expecting numeric in M615 / R615C13: got 'NA'
## Warning: Expecting numeric in N615 / R615C14: got 'NA'
## Warning: Expecting numeric in O615 / R615C15: got 'NA'
## Warning: Expecting numeric in R615 / R615C18: got 'NA'
## Warning: Expecting numeric in S615 / R615C19: got 'NA'
## Warning: Expecting numeric in T615 / R615C20: got 'NA'
## Warning: Expecting numeric in M616 / R616C13: got 'NA'
## Warning: Expecting numeric in N616 / R616C14: got 'NA'
## Warning: Expecting numeric in O616 / R616C15: got 'NA'
## Warning: Expecting numeric in R616 / R616C18: got 'NA'
## Warning: Expecting numeric in S616 / R616C19: got 'NA'
## Warning: Expecting numeric in T616 / R616C20: got 'NA'
## Warning: Expecting numeric in M617 / R617C13: got 'NA'
## Warning: Expecting numeric in N617 / R617C14: got 'NA'
## Warning: Expecting numeric in O617 / R617C15: got 'NA'
## Warning: Expecting numeric in R617 / R617C18: got 'NA'
## Warning: Expecting numeric in S617 / R617C19: got 'NA'
## Warning: Expecting numeric in T617 / R617C20: got 'NA'
## Warning: Expecting numeric in M618 / R618C13: got 'NA'
## Warning: Expecting numeric in N618 / R618C14: got 'NA'
## Warning: Expecting numeric in O618 / R618C15: got 'NA'
## Warning: Expecting numeric in R618 / R618C18: got 'NA'
## Warning: Expecting numeric in S618 / R618C19: got 'NA'
## Warning: Expecting numeric in T618 / R618C20: got 'NA'
## Warning: Expecting numeric in M619 / R619C13: got 'NA'
## Warning: Expecting numeric in N619 / R619C14: got 'NA'
## Warning: Expecting numeric in O619 / R619C15: got 'NA'
## Warning: Expecting numeric in R619 / R619C18: got 'NA'
## Warning: Expecting numeric in S619 / R619C19: got 'NA'
## Warning: Expecting numeric in T619 / R619C20: got 'NA'
## Warning: Expecting numeric in M620 / R620C13: got 'NA'
## Warning: Expecting numeric in N620 / R620C14: got 'NA'
## Warning: Expecting numeric in O620 / R620C15: got 'NA'
## Warning: Expecting numeric in R620 / R620C18: got 'NA'
## Warning: Expecting numeric in S620 / R620C19: got 'NA'
## Warning: Expecting numeric in T620 / R620C20: got 'NA'
## Warning: Expecting numeric in M621 / R621C13: got 'NA'
## Warning: Expecting numeric in N621 / R621C14: got 'NA'
## Warning: Expecting numeric in O621 / R621C15: got 'NA'
## Warning: Expecting numeric in R621 / R621C18: got 'NA'
## Warning: Expecting numeric in S621 / R621C19: got 'NA'
## Warning: Expecting numeric in T621 / R621C20: got 'NA'
## Warning: Expecting numeric in M622 / R622C13: got 'NA'
## Warning: Expecting numeric in N622 / R622C14: got 'NA'
## Warning: Expecting numeric in O622 / R622C15: got 'NA'
## Warning: Expecting numeric in R622 / R622C18: got 'NA'
## Warning: Expecting numeric in S622 / R622C19: got 'NA'
## Warning: Expecting numeric in T622 / R622C20: got 'NA'
## Warning: Expecting numeric in M623 / R623C13: got 'NA'
## Warning: Expecting numeric in N623 / R623C14: got 'NA'
## Warning: Expecting numeric in O623 / R623C15: got 'NA'
## Warning: Expecting numeric in R623 / R623C18: got 'NA'
## Warning: Expecting numeric in S623 / R623C19: got 'NA'
## Warning: Expecting numeric in T623 / R623C20: got 'NA'
## Warning: Expecting numeric in M624 / R624C13: got 'NA'
## Warning: Expecting numeric in N624 / R624C14: got 'NA'
## Warning: Expecting numeric in O624 / R624C15: got 'NA'
## Warning: Expecting numeric in R624 / R624C18: got 'NA'
## Warning: Expecting numeric in S624 / R624C19: got 'NA'
## Warning: Expecting numeric in T624 / R624C20: got 'NA'
## Warning: Expecting numeric in M625 / R625C13: got 'NA'
## Warning: Expecting numeric in N625 / R625C14: got 'NA'
## Warning: Expecting numeric in O625 / R625C15: got 'NA'
## Warning: Expecting numeric in R625 / R625C18: got 'NA'
## Warning: Expecting numeric in S625 / R625C19: got 'NA'
## Warning: Expecting numeric in T625 / R625C20: got 'NA'
## Warning: Expecting numeric in M626 / R626C13: got 'NA'
## Warning: Expecting numeric in N626 / R626C14: got 'NA'
## Warning: Expecting numeric in O626 / R626C15: got 'NA'
## Warning: Expecting numeric in R626 / R626C18: got 'NA'
## Warning: Expecting numeric in S626 / R626C19: got 'NA'
## Warning: Expecting numeric in T626 / R626C20: got 'NA'
## Warning: Expecting numeric in M627 / R627C13: got 'NA'
## Warning: Expecting numeric in N627 / R627C14: got 'NA'
## Warning: Expecting numeric in O627 / R627C15: got 'NA'
## Warning: Expecting numeric in R627 / R627C18: got 'NA'
## Warning: Expecting numeric in S627 / R627C19: got 'NA'
## Warning: Expecting numeric in T627 / R627C20: got 'NA'
## Warning: Expecting numeric in M628 / R628C13: got 'NA'
## Warning: Expecting numeric in N628 / R628C14: got 'NA'
## Warning: Expecting numeric in O628 / R628C15: got 'NA'
## Warning: Expecting numeric in R628 / R628C18: got 'NA'
## Warning: Expecting numeric in S628 / R628C19: got 'NA'
## Warning: Expecting numeric in T628 / R628C20: got 'NA'
## Warning: Expecting numeric in M629 / R629C13: got 'NA'
## Warning: Expecting numeric in N629 / R629C14: got 'NA'
## Warning: Expecting numeric in O629 / R629C15: got 'NA'
## Warning: Expecting numeric in R629 / R629C18: got 'NA'
## Warning: Expecting numeric in S629 / R629C19: got 'NA'
## Warning: Expecting numeric in T629 / R629C20: got 'NA'
## Warning: Expecting numeric in M630 / R630C13: got 'NA'
## Warning: Expecting numeric in N630 / R630C14: got 'NA'
## Warning: Expecting numeric in O630 / R630C15: got 'NA'
## Warning: Expecting numeric in R630 / R630C18: got 'NA'
## Warning: Expecting numeric in S630 / R630C19: got 'NA'
## Warning: Expecting numeric in T630 / R630C20: got 'NA'
## Warning: Expecting numeric in M631 / R631C13: got 'NA'
## Warning: Expecting numeric in N631 / R631C14: got 'NA'
## Warning: Expecting numeric in O631 / R631C15: got 'NA'
## Warning: Expecting numeric in R631 / R631C18: got 'NA'
## Warning: Expecting numeric in S631 / R631C19: got 'NA'
## Warning: Expecting numeric in T631 / R631C20: got 'NA'
## Warning: Expecting numeric in M632 / R632C13: got 'NA'
## Warning: Expecting numeric in N632 / R632C14: got 'NA'
## Warning: Expecting numeric in O632 / R632C15: got 'NA'
## Warning: Expecting numeric in R632 / R632C18: got 'NA'
## Warning: Expecting numeric in S632 / R632C19: got 'NA'
## Warning: Expecting numeric in T632 / R632C20: got 'NA'
## Warning: Expecting numeric in M633 / R633C13: got 'NA'
## Warning: Expecting numeric in N633 / R633C14: got 'NA'
## Warning: Expecting numeric in O633 / R633C15: got 'NA'
## Warning: Expecting numeric in R633 / R633C18: got 'NA'
## Warning: Expecting numeric in S633 / R633C19: got 'NA'
## Warning: Expecting numeric in T633 / R633C20: got 'NA'
## Warning: Expecting numeric in M634 / R634C13: got 'NA'
## Warning: Expecting numeric in N634 / R634C14: got 'NA'
## Warning: Expecting numeric in O634 / R634C15: got 'NA'
## Warning: Expecting numeric in R634 / R634C18: got 'NA'
## Warning: Expecting numeric in S634 / R634C19: got 'NA'
## Warning: Expecting numeric in T634 / R634C20: got 'NA'
## Warning: Expecting numeric in M635 / R635C13: got 'NA'
## Warning: Expecting numeric in N635 / R635C14: got 'NA'
## Warning: Expecting numeric in O635 / R635C15: got 'NA'
## Warning: Expecting numeric in R635 / R635C18: got 'NA'
## Warning: Expecting numeric in S635 / R635C19: got 'NA'
## Warning: Expecting numeric in T635 / R635C20: got 'NA'
## Warning: Expecting numeric in M636 / R636C13: got 'NA'
## Warning: Expecting numeric in N636 / R636C14: got 'NA'
## Warning: Expecting numeric in O636 / R636C15: got 'NA'
## Warning: Expecting numeric in R636 / R636C18: got 'NA'
## Warning: Expecting numeric in S636 / R636C19: got 'NA'
## Warning: Expecting numeric in T636 / R636C20: got 'NA'
## Warning: Expecting numeric in M637 / R637C13: got 'NA'
## Warning: Expecting numeric in N637 / R637C14: got 'NA'
## Warning: Expecting numeric in O637 / R637C15: got 'NA'
## Warning: Expecting numeric in R637 / R637C18: got 'NA'
## Warning: Expecting numeric in S637 / R637C19: got 'NA'
## Warning: Expecting numeric in T637 / R637C20: got 'NA'
## Warning: Expecting numeric in M638 / R638C13: got 'NA'
## Warning: Expecting numeric in N638 / R638C14: got 'NA'
## Warning: Expecting numeric in O638 / R638C15: got 'NA'
## Warning: Expecting numeric in R638 / R638C18: got 'NA'
## Warning: Expecting numeric in S638 / R638C19: got 'NA'
## Warning: Expecting numeric in T638 / R638C20: got 'NA'
## Warning: Expecting numeric in M639 / R639C13: got 'NA'
## Warning: Expecting numeric in N639 / R639C14: got 'NA'
## Warning: Expecting numeric in O639 / R639C15: got 'NA'
## Warning: Expecting numeric in R639 / R639C18: got 'NA'
## Warning: Expecting numeric in S639 / R639C19: got 'NA'
## Warning: Expecting numeric in T639 / R639C20: got 'NA'
## Warning: Expecting numeric in M640 / R640C13: got 'NA'
## Warning: Expecting numeric in N640 / R640C14: got 'NA'
## Warning: Expecting numeric in O640 / R640C15: got 'NA'
## Warning: Expecting numeric in R640 / R640C18: got 'NA'
## Warning: Expecting numeric in S640 / R640C19: got 'NA'
## Warning: Expecting numeric in T640 / R640C20: got 'NA'
## Warning: Expecting numeric in M641 / R641C13: got 'NA'
## Warning: Expecting numeric in N641 / R641C14: got 'NA'
## Warning: Expecting numeric in O641 / R641C15: got 'NA'
## Warning: Expecting numeric in R641 / R641C18: got 'NA'
## Warning: Expecting numeric in S641 / R641C19: got 'NA'
## Warning: Expecting numeric in T641 / R641C20: got 'NA'
## Warning: Expecting numeric in M642 / R642C13: got 'NA'
## Warning: Expecting numeric in N642 / R642C14: got 'NA'
## Warning: Expecting numeric in O642 / R642C15: got 'NA'
## Warning: Expecting numeric in R642 / R642C18: got 'NA'
## Warning: Expecting numeric in S642 / R642C19: got 'NA'
## Warning: Expecting numeric in T642 / R642C20: got 'NA'
## Warning: Expecting numeric in M643 / R643C13: got 'NA'
## Warning: Expecting numeric in N643 / R643C14: got 'NA'
## Warning: Expecting numeric in O643 / R643C15: got 'NA'
## Warning: Expecting numeric in R643 / R643C18: got 'NA'
## Warning: Expecting numeric in S643 / R643C19: got 'NA'
## Warning: Expecting numeric in T643 / R643C20: got 'NA'
## Warning: Expecting numeric in M644 / R644C13: got 'NA'
## Warning: Expecting numeric in N644 / R644C14: got 'NA'
## Warning: Expecting numeric in O644 / R644C15: got 'NA'
## Warning: Expecting numeric in R644 / R644C18: got 'NA'
## Warning: Expecting numeric in S644 / R644C19: got 'NA'
## Warning: Expecting numeric in T644 / R644C20: got 'NA'
## Warning: Expecting numeric in M645 / R645C13: got 'NA'
## Warning: Expecting numeric in N645 / R645C14: got 'NA'
## Warning: Expecting numeric in O645 / R645C15: got 'NA'
## Warning: Expecting numeric in R645 / R645C18: got 'NA'
## Warning: Expecting numeric in S645 / R645C19: got 'NA'
## Warning: Expecting numeric in T645 / R645C20: got 'NA'
## Warning: Expecting numeric in M646 / R646C13: got 'NA'
## Warning: Expecting numeric in N646 / R646C14: got 'NA'
## Warning: Expecting numeric in O646 / R646C15: got 'NA'
## Warning: Expecting numeric in R646 / R646C18: got 'NA'
## Warning: Expecting numeric in S646 / R646C19: got 'NA'
## Warning: Expecting numeric in T646 / R646C20: got 'NA'
## Warning: Expecting numeric in M647 / R647C13: got 'NA'
## Warning: Expecting numeric in N647 / R647C14: got 'NA'
## Warning: Expecting numeric in O647 / R647C15: got 'NA'
## Warning: Expecting numeric in R647 / R647C18: got 'NA'
## Warning: Expecting numeric in S647 / R647C19: got 'NA'
## Warning: Expecting numeric in T647 / R647C20: got 'NA'
## Warning: Expecting numeric in M648 / R648C13: got 'NA'
## Warning: Expecting numeric in N648 / R648C14: got 'NA'
## Warning: Expecting numeric in O648 / R648C15: got 'NA'
## Warning: Expecting numeric in R648 / R648C18: got 'NA'
## Warning: Expecting numeric in S648 / R648C19: got 'NA'
## Warning: Expecting numeric in T648 / R648C20: got 'NA'
## Warning: Expecting numeric in M649 / R649C13: got 'NA'
## Warning: Expecting numeric in N649 / R649C14: got 'NA'
## Warning: Expecting numeric in O649 / R649C15: got 'NA'
## Warning: Expecting numeric in R649 / R649C18: got 'NA'
## Warning: Expecting numeric in S649 / R649C19: got 'NA'
## Warning: Expecting numeric in T649 / R649C20: got 'NA'
## Warning: Expecting numeric in M650 / R650C13: got 'NA'
## Warning: Expecting numeric in N650 / R650C14: got 'NA'
## Warning: Expecting numeric in O650 / R650C15: got 'NA'
## Warning: Expecting numeric in R650 / R650C18: got 'NA'
## Warning: Expecting numeric in S650 / R650C19: got 'NA'
## Warning: Expecting numeric in T650 / R650C20: got 'NA'
## Warning: Expecting numeric in M651 / R651C13: got 'NA'
## Warning: Expecting numeric in N651 / R651C14: got 'NA'
## Warning: Expecting numeric in O651 / R651C15: got 'NA'
## Warning: Expecting numeric in R651 / R651C18: got 'NA'
## Warning: Expecting numeric in S651 / R651C19: got 'NA'
## Warning: Expecting numeric in T651 / R651C20: got 'NA'
## Warning: Expecting numeric in M652 / R652C13: got 'NA'
## Warning: Expecting numeric in N652 / R652C14: got 'NA'
## Warning: Expecting numeric in O652 / R652C15: got 'NA'
## Warning: Expecting numeric in R652 / R652C18: got 'NA'
## Warning: Expecting numeric in S652 / R652C19: got 'NA'
## Warning: Expecting numeric in T652 / R652C20: got 'NA'
## Warning: Expecting numeric in M653 / R653C13: got 'NA'
## Warning: Expecting numeric in N653 / R653C14: got 'NA'
## Warning: Expecting numeric in O653 / R653C15: got 'NA'
## Warning: Expecting numeric in R653 / R653C18: got 'NA'
## Warning: Expecting numeric in S653 / R653C19: got 'NA'
## Warning: Expecting numeric in T653 / R653C20: got 'NA'
## Warning: Expecting numeric in M654 / R654C13: got 'NA'
## Warning: Expecting numeric in N654 / R654C14: got 'NA'
## Warning: Expecting numeric in O654 / R654C15: got 'NA'
## Warning: Expecting numeric in R654 / R654C18: got 'NA'
## Warning: Expecting numeric in S654 / R654C19: got 'NA'
## Warning: Expecting numeric in T654 / R654C20: got 'NA'
## Warning: Expecting numeric in M655 / R655C13: got 'NA'
## Warning: Expecting numeric in N655 / R655C14: got 'NA'
## Warning: Expecting numeric in O655 / R655C15: got 'NA'
## Warning: Expecting numeric in R655 / R655C18: got 'NA'
## Warning: Expecting numeric in S655 / R655C19: got 'NA'
## Warning: Expecting numeric in T655 / R655C20: got 'NA'
## Warning: Expecting numeric in M656 / R656C13: got 'NA'
## Warning: Expecting numeric in N656 / R656C14: got 'NA'
## Warning: Expecting numeric in O656 / R656C15: got 'NA'
## Warning: Expecting numeric in R656 / R656C18: got 'NA'
## Warning: Expecting numeric in S656 / R656C19: got 'NA'
## Warning: Expecting numeric in T656 / R656C20: got 'NA'
## Warning: Expecting numeric in M657 / R657C13: got 'NA'
## Warning: Expecting numeric in N657 / R657C14: got 'NA'
## Warning: Expecting numeric in O657 / R657C15: got 'NA'
## Warning: Expecting numeric in R657 / R657C18: got 'NA'
## Warning: Expecting numeric in S657 / R657C19: got 'NA'
## Warning: Expecting numeric in T657 / R657C20: got 'NA'
## Warning: Expecting numeric in M658 / R658C13: got 'NA'
## Warning: Expecting numeric in N658 / R658C14: got 'NA'
## Warning: Expecting numeric in O658 / R658C15: got 'NA'
## Warning: Expecting numeric in R658 / R658C18: got 'NA'
## Warning: Expecting numeric in S658 / R658C19: got 'NA'
## Warning: Expecting numeric in T658 / R658C20: got 'NA'
## Warning: Expecting numeric in M659 / R659C13: got 'NA'
## Warning: Expecting numeric in N659 / R659C14: got 'NA'
## Warning: Expecting numeric in O659 / R659C15: got 'NA'
## Warning: Expecting numeric in R659 / R659C18: got 'NA'
## Warning: Expecting numeric in S659 / R659C19: got 'NA'
## Warning: Expecting numeric in T659 / R659C20: got 'NA'
## Warning: Expecting numeric in M660 / R660C13: got 'NA'
## Warning: Expecting numeric in N660 / R660C14: got 'NA'
## Warning: Expecting numeric in O660 / R660C15: got 'NA'
## Warning: Expecting numeric in R660 / R660C18: got 'NA'
## Warning: Expecting numeric in S660 / R660C19: got 'NA'
## Warning: Expecting numeric in T660 / R660C20: got 'NA'
## Warning: Expecting numeric in M661 / R661C13: got 'NA'
## Warning: Expecting numeric in N661 / R661C14: got 'NA'
## Warning: Expecting numeric in O661 / R661C15: got 'NA'
## Warning: Expecting numeric in R661 / R661C18: got 'NA'
## Warning: Expecting numeric in S661 / R661C19: got 'NA'
## Warning: Expecting numeric in T661 / R661C20: got 'NA'
## Warning: Expecting numeric in M662 / R662C13: got 'NA'
## Warning: Expecting numeric in N662 / R662C14: got 'NA'
## Warning: Expecting numeric in O662 / R662C15: got 'NA'
## Warning: Expecting numeric in R662 / R662C18: got 'NA'
## Warning: Expecting numeric in S662 / R662C19: got 'NA'
## Warning: Expecting numeric in T662 / R662C20: got 'NA'
## Warning: Expecting numeric in M663 / R663C13: got 'NA'
## Warning: Expecting numeric in N663 / R663C14: got 'NA'
## Warning: Expecting numeric in O663 / R663C15: got 'NA'
## Warning: Expecting numeric in R663 / R663C18: got 'NA'
## Warning: Expecting numeric in S663 / R663C19: got 'NA'
## Warning: Expecting numeric in T663 / R663C20: got 'NA'
## Warning: Expecting numeric in M664 / R664C13: got 'NA'
## Warning: Expecting numeric in N664 / R664C14: got 'NA'
## Warning: Expecting numeric in O664 / R664C15: got 'NA'
## Warning: Expecting numeric in R664 / R664C18: got 'NA'
## Warning: Expecting numeric in S664 / R664C19: got 'NA'
## Warning: Expecting numeric in T664 / R664C20: got 'NA'
## Warning: Expecting numeric in M665 / R665C13: got 'NA'
## Warning: Expecting numeric in N665 / R665C14: got 'NA'
## Warning: Expecting numeric in O665 / R665C15: got 'NA'
## Warning: Expecting numeric in R665 / R665C18: got 'NA'
## Warning: Expecting numeric in S665 / R665C19: got 'NA'
## Warning: Expecting numeric in T665 / R665C20: got 'NA'
## Warning: Expecting numeric in M666 / R666C13: got 'NA'
## Warning: Expecting numeric in N666 / R666C14: got 'NA'
## Warning: Expecting numeric in O666 / R666C15: got 'NA'
## Warning: Expecting numeric in R666 / R666C18: got 'NA'
## Warning: Expecting numeric in S666 / R666C19: got 'NA'
## Warning: Expecting numeric in T666 / R666C20: got 'NA'
## Warning: Expecting numeric in M667 / R667C13: got 'NA'
## Warning: Expecting numeric in N667 / R667C14: got 'NA'
## Warning: Expecting numeric in O667 / R667C15: got 'NA'
## Warning: Expecting numeric in R667 / R667C18: got 'NA'
## Warning: Expecting numeric in S667 / R667C19: got 'NA'
## Warning: Expecting numeric in T667 / R667C20: got 'NA'
## Warning: Expecting numeric in M668 / R668C13: got 'NA'
## Warning: Expecting numeric in N668 / R668C14: got 'NA'
## Warning: Expecting numeric in O668 / R668C15: got 'NA'
## Warning: Expecting numeric in R668 / R668C18: got 'NA'
## Warning: Expecting numeric in S668 / R668C19: got 'NA'
## Warning: Expecting numeric in T668 / R668C20: got 'NA'
## Warning: Expecting numeric in M669 / R669C13: got 'NA'
## Warning: Expecting numeric in N669 / R669C14: got 'NA'
## Warning: Expecting numeric in O669 / R669C15: got 'NA'
## Warning: Expecting numeric in R669 / R669C18: got 'NA'
## Warning: Expecting numeric in S669 / R669C19: got 'NA'
## Warning: Expecting numeric in T669 / R669C20: got 'NA'
## Warning: Expecting numeric in M670 / R670C13: got 'NA'
## Warning: Expecting numeric in N670 / R670C14: got 'NA'
## Warning: Expecting numeric in O670 / R670C15: got 'NA'
## Warning: Expecting numeric in R670 / R670C18: got 'NA'
## Warning: Expecting numeric in S670 / R670C19: got 'NA'
## Warning: Expecting numeric in T670 / R670C20: got 'NA'
## Warning: Expecting numeric in M671 / R671C13: got 'NA'
## Warning: Expecting numeric in N671 / R671C14: got 'NA'
## Warning: Expecting numeric in O671 / R671C15: got 'NA'
## Warning: Expecting numeric in R671 / R671C18: got 'NA'
## Warning: Expecting numeric in S671 / R671C19: got 'NA'
## Warning: Expecting numeric in T671 / R671C20: got 'NA'
## Warning: Expecting numeric in M672 / R672C13: got 'NA'
## Warning: Expecting numeric in N672 / R672C14: got 'NA'
## Warning: Expecting numeric in O672 / R672C15: got 'NA'
## Warning: Expecting numeric in R672 / R672C18: got 'NA'
## Warning: Expecting numeric in S672 / R672C19: got 'NA'
## Warning: Expecting numeric in T672 / R672C20: got 'NA'
## Warning: Expecting numeric in M673 / R673C13: got 'NA'
## Warning: Expecting numeric in N673 / R673C14: got 'NA'
## Warning: Expecting numeric in O673 / R673C15: got 'NA'
## Warning: Expecting numeric in R673 / R673C18: got 'NA'
## Warning: Expecting numeric in S673 / R673C19: got 'NA'
## Warning: Expecting numeric in T673 / R673C20: got 'NA'
## Warning: Expecting numeric in M674 / R674C13: got 'NA'
## Warning: Expecting numeric in N674 / R674C14: got 'NA'
## Warning: Expecting numeric in O674 / R674C15: got 'NA'
## Warning: Expecting numeric in R674 / R674C18: got 'NA'
## Warning: Expecting numeric in S674 / R674C19: got 'NA'
## Warning: Expecting numeric in T674 / R674C20: got 'NA'
## Warning: Expecting numeric in M675 / R675C13: got 'NA'
## Warning: Expecting numeric in N675 / R675C14: got 'NA'
## Warning: Expecting numeric in O675 / R675C15: got 'NA'
## Warning: Expecting numeric in R675 / R675C18: got 'NA'
## Warning: Expecting numeric in S675 / R675C19: got 'NA'
## Warning: Expecting numeric in T675 / R675C20: got 'NA'
## Warning: Expecting numeric in M676 / R676C13: got 'NA'
## Warning: Expecting numeric in N676 / R676C14: got 'NA'
## Warning: Expecting numeric in O676 / R676C15: got 'NA'
## Warning: Expecting numeric in R676 / R676C18: got 'NA'
## Warning: Expecting numeric in S676 / R676C19: got 'NA'
## Warning: Expecting numeric in T676 / R676C20: got 'NA'
## Warning: Expecting numeric in M677 / R677C13: got 'NA'
## Warning: Expecting numeric in N677 / R677C14: got 'NA'
## Warning: Expecting numeric in O677 / R677C15: got 'NA'
## Warning: Expecting numeric in R677 / R677C18: got 'NA'
## Warning: Expecting numeric in S677 / R677C19: got 'NA'
## Warning: Expecting numeric in T677 / R677C20: got 'NA'
## Warning: Expecting numeric in M678 / R678C13: got 'NA'
## Warning: Expecting numeric in N678 / R678C14: got 'NA'
## Warning: Expecting numeric in O678 / R678C15: got 'NA'
## Warning: Expecting numeric in R678 / R678C18: got 'NA'
## Warning: Expecting numeric in S678 / R678C19: got 'NA'
## Warning: Expecting numeric in T678 / R678C20: got 'NA'
## Warning: Expecting numeric in M679 / R679C13: got 'NA'
## Warning: Expecting numeric in N679 / R679C14: got 'NA'
## Warning: Expecting numeric in O679 / R679C15: got 'NA'
## Warning: Expecting numeric in R679 / R679C18: got 'NA'
## Warning: Expecting numeric in S679 / R679C19: got 'NA'
## Warning: Expecting numeric in T679 / R679C20: got 'NA'
## Warning: Expecting numeric in M680 / R680C13: got 'NA'
## Warning: Expecting numeric in N680 / R680C14: got 'NA'
## Warning: Expecting numeric in O680 / R680C15: got 'NA'
## Warning: Expecting numeric in R680 / R680C18: got 'NA'
## Warning: Expecting numeric in S680 / R680C19: got 'NA'
## Warning: Expecting numeric in T680 / R680C20: got 'NA'
## Warning: Expecting numeric in M681 / R681C13: got 'NA'
## Warning: Expecting numeric in N681 / R681C14: got 'NA'
## Warning: Expecting numeric in O681 / R681C15: got 'NA'
## Warning: Expecting numeric in R681 / R681C18: got 'NA'
## Warning: Expecting numeric in S681 / R681C19: got 'NA'
## Warning: Expecting numeric in T681 / R681C20: got 'NA'
## Warning: Expecting numeric in M682 / R682C13: got 'NA'
## Warning: Expecting numeric in N682 / R682C14: got 'NA'
## Warning: Expecting numeric in O682 / R682C15: got 'NA'
## Warning: Expecting numeric in R682 / R682C18: got 'NA'
## Warning: Expecting numeric in S682 / R682C19: got 'NA'
## Warning: Expecting numeric in T682 / R682C20: got 'NA'
## Warning: Expecting numeric in M683 / R683C13: got 'NA'
## Warning: Expecting numeric in N683 / R683C14: got 'NA'
## Warning: Expecting numeric in O683 / R683C15: got 'NA'
## Warning: Expecting numeric in R683 / R683C18: got 'NA'
## Warning: Expecting numeric in S683 / R683C19: got 'NA'
## Warning: Expecting numeric in T683 / R683C20: got 'NA'
## Warning: Expecting numeric in M684 / R684C13: got 'NA'
## Warning: Expecting numeric in N684 / R684C14: got 'NA'
## Warning: Expecting numeric in O684 / R684C15: got 'NA'
## Warning: Expecting numeric in R684 / R684C18: got 'NA'
## Warning: Expecting numeric in S684 / R684C19: got 'NA'
## Warning: Expecting numeric in T684 / R684C20: got 'NA'
## Warning: Expecting numeric in M685 / R685C13: got 'NA'
## Warning: Expecting numeric in N685 / R685C14: got 'NA'
## Warning: Expecting numeric in O685 / R685C15: got 'NA'
## Warning: Expecting numeric in R685 / R685C18: got 'NA'
## Warning: Expecting numeric in S685 / R685C19: got 'NA'
## Warning: Expecting numeric in T685 / R685C20: got 'NA'
## Warning: Expecting numeric in M686 / R686C13: got 'NA'
## Warning: Expecting numeric in N686 / R686C14: got 'NA'
## Warning: Expecting numeric in O686 / R686C15: got 'NA'
## Warning: Expecting numeric in R686 / R686C18: got 'NA'
## Warning: Expecting numeric in S686 / R686C19: got 'NA'
## Warning: Expecting numeric in T686 / R686C20: got 'NA'
## Warning: Expecting numeric in M687 / R687C13: got 'NA'
## Warning: Expecting numeric in N687 / R687C14: got 'NA'
## Warning: Expecting numeric in O687 / R687C15: got 'NA'
## Warning: Expecting numeric in R687 / R687C18: got 'NA'
## Warning: Expecting numeric in S687 / R687C19: got 'NA'
## Warning: Expecting numeric in T687 / R687C20: got 'NA'
## Warning: Expecting numeric in M688 / R688C13: got 'NA'
## Warning: Expecting numeric in N688 / R688C14: got 'NA'
## Warning: Expecting numeric in O688 / R688C15: got 'NA'
## Warning: Expecting numeric in R688 / R688C18: got 'NA'
## Warning: Expecting numeric in S688 / R688C19: got 'NA'
## Warning: Expecting numeric in T688 / R688C20: got 'NA'
## Warning: Expecting numeric in M689 / R689C13: got 'NA'
## Warning: Expecting numeric in N689 / R689C14: got 'NA'
## Warning: Expecting numeric in O689 / R689C15: got 'NA'
## Warning: Expecting numeric in R689 / R689C18: got 'NA'
## Warning: Expecting numeric in S689 / R689C19: got 'NA'
## Warning: Expecting numeric in T689 / R689C20: got 'NA'
## Warning: Expecting numeric in M690 / R690C13: got 'NA'
## Warning: Expecting numeric in N690 / R690C14: got 'NA'
## Warning: Expecting numeric in O690 / R690C15: got 'NA'
## Warning: Expecting numeric in R690 / R690C18: got 'NA'
## Warning: Expecting numeric in S690 / R690C19: got 'NA'
## Warning: Expecting numeric in T690 / R690C20: got 'NA'
## Warning: Expecting numeric in M691 / R691C13: got 'NA'
## Warning: Expecting numeric in N691 / R691C14: got 'NA'
## Warning: Expecting numeric in O691 / R691C15: got 'NA'
## Warning: Expecting numeric in R691 / R691C18: got 'NA'
## Warning: Expecting numeric in S691 / R691C19: got 'NA'
## Warning: Expecting numeric in T691 / R691C20: got 'NA'
## Warning: Expecting numeric in M692 / R692C13: got 'NA'
## Warning: Expecting numeric in N692 / R692C14: got 'NA'
## Warning: Expecting numeric in O692 / R692C15: got 'NA'
## Warning: Expecting numeric in R692 / R692C18: got 'NA'
## Warning: Expecting numeric in S692 / R692C19: got 'NA'
## Warning: Expecting numeric in T692 / R692C20: got 'NA'
## Warning: Expecting numeric in M693 / R693C13: got 'NA'
## Warning: Expecting numeric in N693 / R693C14: got 'NA'
## Warning: Expecting numeric in O693 / R693C15: got 'NA'
## Warning: Expecting numeric in R693 / R693C18: got 'NA'
## Warning: Expecting numeric in S693 / R693C19: got 'NA'
## Warning: Expecting numeric in T693 / R693C20: got 'NA'
## Warning: Expecting numeric in M694 / R694C13: got 'NA'
## Warning: Expecting numeric in N694 / R694C14: got 'NA'
## Warning: Expecting numeric in O694 / R694C15: got 'NA'
## Warning: Expecting numeric in R694 / R694C18: got 'NA'
## Warning: Expecting numeric in S694 / R694C19: got 'NA'
## Warning: Expecting numeric in T694 / R694C20: got 'NA'
## Warning: Expecting numeric in M695 / R695C13: got 'NA'
## Warning: Expecting numeric in N695 / R695C14: got 'NA'
## Warning: Expecting numeric in O695 / R695C15: got 'NA'
## Warning: Expecting numeric in R695 / R695C18: got 'NA'
## Warning: Expecting numeric in S695 / R695C19: got 'NA'
## Warning: Expecting numeric in T695 / R695C20: got 'NA'
## Warning: Expecting numeric in M696 / R696C13: got 'NA'
## Warning: Expecting numeric in N696 / R696C14: got 'NA'
## Warning: Expecting numeric in O696 / R696C15: got 'NA'
## Warning: Expecting numeric in R696 / R696C18: got 'NA'
## Warning: Expecting numeric in S696 / R696C19: got 'NA'
## Warning: Expecting numeric in T696 / R696C20: got 'NA'
## Warning: Expecting numeric in M697 / R697C13: got 'NA'
## Warning: Expecting numeric in N697 / R697C14: got 'NA'
## Warning: Expecting numeric in O697 / R697C15: got 'NA'
## Warning: Expecting numeric in R697 / R697C18: got 'NA'
## Warning: Expecting numeric in S697 / R697C19: got 'NA'
## Warning: Expecting numeric in T697 / R697C20: got 'NA'
## Warning: Expecting numeric in M698 / R698C13: got 'NA'
## Warning: Expecting numeric in N698 / R698C14: got 'NA'
## Warning: Expecting numeric in O698 / R698C15: got 'NA'
## Warning: Expecting numeric in R698 / R698C18: got 'NA'
## Warning: Expecting numeric in S698 / R698C19: got 'NA'
## Warning: Expecting numeric in T698 / R698C20: got 'NA'
## Warning: Expecting numeric in M699 / R699C13: got 'NA'
## Warning: Expecting numeric in N699 / R699C14: got 'NA'
## Warning: Expecting numeric in O699 / R699C15: got 'NA'
## Warning: Expecting numeric in R699 / R699C18: got 'NA'
## Warning: Expecting numeric in S699 / R699C19: got 'NA'
## Warning: Expecting numeric in T699 / R699C20: got 'NA'
## Warning: Expecting numeric in M700 / R700C13: got 'NA'
## Warning: Expecting numeric in N700 / R700C14: got 'NA'
## Warning: Expecting numeric in O700 / R700C15: got 'NA'
## Warning: Expecting numeric in R700 / R700C18: got 'NA'
## Warning: Expecting numeric in S700 / R700C19: got 'NA'
## Warning: Expecting numeric in T700 / R700C20: got 'NA'
## Warning: Expecting numeric in M701 / R701C13: got 'NA'
## Warning: Expecting numeric in N701 / R701C14: got 'NA'
## Warning: Expecting numeric in O701 / R701C15: got 'NA'
## Warning: Expecting numeric in R701 / R701C18: got 'NA'
## Warning: Expecting numeric in S701 / R701C19: got 'NA'
## Warning: Expecting numeric in T701 / R701C20: got 'NA'
## Warning: Expecting numeric in M702 / R702C13: got 'NA'
## Warning: Expecting numeric in N702 / R702C14: got 'NA'
## Warning: Expecting numeric in O702 / R702C15: got 'NA'
## Warning: Expecting numeric in R702 / R702C18: got 'NA'
## Warning: Expecting numeric in S702 / R702C19: got 'NA'
## Warning: Expecting numeric in T702 / R702C20: got 'NA'
## Warning: Expecting numeric in M703 / R703C13: got 'NA'
## Warning: Expecting numeric in N703 / R703C14: got 'NA'
## Warning: Expecting numeric in O703 / R703C15: got 'NA'
## Warning: Expecting numeric in R703 / R703C18: got 'NA'
## Warning: Expecting numeric in S703 / R703C19: got 'NA'
## Warning: Expecting numeric in T703 / R703C20: got 'NA'
## Warning: Expecting numeric in M704 / R704C13: got 'NA'
## Warning: Expecting numeric in N704 / R704C14: got 'NA'
## Warning: Expecting numeric in O704 / R704C15: got 'NA'
## Warning: Expecting numeric in R704 / R704C18: got 'NA'
## Warning: Expecting numeric in S704 / R704C19: got 'NA'
## Warning: Expecting numeric in T704 / R704C20: got 'NA'
## Warning: Expecting numeric in M705 / R705C13: got 'NA'
## Warning: Expecting numeric in N705 / R705C14: got 'NA'
## Warning: Expecting numeric in O705 / R705C15: got 'NA'
## Warning: Expecting numeric in R705 / R705C18: got 'NA'
## Warning: Expecting numeric in S705 / R705C19: got 'NA'
## Warning: Expecting numeric in T705 / R705C20: got 'NA'
## Warning: Expecting numeric in M706 / R706C13: got 'NA'
## Warning: Expecting numeric in N706 / R706C14: got 'NA'
## Warning: Expecting numeric in O706 / R706C15: got 'NA'
## Warning: Expecting numeric in R706 / R706C18: got 'NA'
## Warning: Expecting numeric in S706 / R706C19: got 'NA'
## Warning: Expecting numeric in T706 / R706C20: got 'NA'
## Warning: Expecting numeric in M707 / R707C13: got 'NA'
## Warning: Expecting numeric in N707 / R707C14: got 'NA'
## Warning: Expecting numeric in O707 / R707C15: got 'NA'
## Warning: Expecting numeric in R707 / R707C18: got 'NA'
## Warning: Expecting numeric in S707 / R707C19: got 'NA'
## Warning: Expecting numeric in T707 / R707C20: got 'NA'
## Warning: Expecting numeric in M708 / R708C13: got 'NA'
## Warning: Expecting numeric in N708 / R708C14: got 'NA'
## Warning: Expecting numeric in O708 / R708C15: got 'NA'
## Warning: Expecting numeric in R708 / R708C18: got 'NA'
## Warning: Expecting numeric in S708 / R708C19: got 'NA'
## Warning: Expecting numeric in T708 / R708C20: got 'NA'
## Warning: Expecting numeric in M709 / R709C13: got 'NA'
## Warning: Expecting numeric in N709 / R709C14: got 'NA'
## Warning: Expecting numeric in O709 / R709C15: got 'NA'
## Warning: Expecting numeric in R709 / R709C18: got 'NA'
## Warning: Expecting numeric in S709 / R709C19: got 'NA'
## Warning: Expecting numeric in T709 / R709C20: got 'NA'
## Warning: Expecting numeric in M710 / R710C13: got 'NA'
## Warning: Expecting numeric in N710 / R710C14: got 'NA'
## Warning: Expecting numeric in O710 / R710C15: got 'NA'
## Warning: Expecting numeric in R710 / R710C18: got 'NA'
## Warning: Expecting numeric in S710 / R710C19: got 'NA'
## Warning: Expecting numeric in T710 / R710C20: got 'NA'
## Warning: Expecting numeric in M711 / R711C13: got 'NA'
## Warning: Expecting numeric in N711 / R711C14: got 'NA'
## Warning: Expecting numeric in O711 / R711C15: got 'NA'
## Warning: Expecting numeric in R711 / R711C18: got 'NA'
## Warning: Expecting numeric in S711 / R711C19: got 'NA'
## Warning: Expecting numeric in T711 / R711C20: got 'NA'
## Warning: Expecting numeric in M712 / R712C13: got 'NA'
## Warning: Expecting numeric in N712 / R712C14: got 'NA'
## Warning: Expecting numeric in O712 / R712C15: got 'NA'
## Warning: Expecting numeric in R712 / R712C18: got 'NA'
## Warning: Expecting numeric in S712 / R712C19: got 'NA'
## Warning: Expecting numeric in T712 / R712C20: got 'NA'
## Warning: Expecting numeric in M713 / R713C13: got 'NA'
## Warning: Expecting numeric in N713 / R713C14: got 'NA'
## Warning: Expecting numeric in O713 / R713C15: got 'NA'
## Warning: Expecting numeric in R713 / R713C18: got 'NA'
## Warning: Expecting numeric in S713 / R713C19: got 'NA'
## Warning: Expecting numeric in T713 / R713C20: got 'NA'
## Warning: Expecting numeric in M714 / R714C13: got 'NA'
## Warning: Expecting numeric in N714 / R714C14: got 'NA'
## Warning: Expecting numeric in O714 / R714C15: got 'NA'
## Warning: Expecting numeric in R714 / R714C18: got 'NA'
## Warning: Expecting numeric in S714 / R714C19: got 'NA'
## Warning: Expecting numeric in T714 / R714C20: got 'NA'
## Warning: Expecting numeric in M715 / R715C13: got 'NA'
## Warning: Expecting numeric in N715 / R715C14: got 'NA'
## Warning: Expecting numeric in O715 / R715C15: got 'NA'
## Warning: Expecting numeric in R715 / R715C18: got 'NA'
## Warning: Expecting numeric in S715 / R715C19: got 'NA'
## Warning: Expecting numeric in T715 / R715C20: got 'NA'
## Warning: Expecting numeric in M716 / R716C13: got 'NA'
## Warning: Expecting numeric in N716 / R716C14: got 'NA'
## Warning: Expecting numeric in O716 / R716C15: got 'NA'
## Warning: Expecting numeric in R716 / R716C18: got 'NA'
## Warning: Expecting numeric in S716 / R716C19: got 'NA'
## Warning: Expecting numeric in T716 / R716C20: got 'NA'
## Warning: Expecting numeric in M717 / R717C13: got 'NA'
## Warning: Expecting numeric in N717 / R717C14: got 'NA'
## Warning: Expecting numeric in O717 / R717C15: got 'NA'
## Warning: Expecting numeric in R717 / R717C18: got 'NA'
## Warning: Expecting numeric in S717 / R717C19: got 'NA'
## Warning: Expecting numeric in T717 / R717C20: got 'NA'
## Warning: Expecting numeric in M718 / R718C13: got 'NA'
## Warning: Expecting numeric in N718 / R718C14: got 'NA'
## Warning: Expecting numeric in O718 / R718C15: got 'NA'
## Warning: Expecting numeric in R718 / R718C18: got 'NA'
## Warning: Expecting numeric in S718 / R718C19: got 'NA'
## Warning: Expecting numeric in T718 / R718C20: got 'NA'
## Warning: Expecting numeric in M719 / R719C13: got 'NA'
## Warning: Expecting numeric in N719 / R719C14: got 'NA'
## Warning: Expecting numeric in O719 / R719C15: got 'NA'
## Warning: Expecting numeric in R719 / R719C18: got 'NA'
## Warning: Expecting numeric in S719 / R719C19: got 'NA'
## Warning: Expecting numeric in T719 / R719C20: got 'NA'
## Warning: Expecting numeric in M720 / R720C13: got 'NA'
## Warning: Expecting numeric in N720 / R720C14: got 'NA'
## Warning: Expecting numeric in O720 / R720C15: got 'NA'
## Warning: Expecting numeric in R720 / R720C18: got 'NA'
## Warning: Expecting numeric in S720 / R720C19: got 'NA'
## Warning: Expecting numeric in T720 / R720C20: got 'NA'
## Warning: Expecting numeric in M721 / R721C13: got 'NA'
## Warning: Expecting numeric in N721 / R721C14: got 'NA'
## Warning: Expecting numeric in O721 / R721C15: got 'NA'
## Warning: Expecting numeric in R721 / R721C18: got 'NA'
## Warning: Expecting numeric in S721 / R721C19: got 'NA'
## Warning: Expecting numeric in T721 / R721C20: got 'NA'
## Warning: Expecting numeric in M722 / R722C13: got 'NA'
## Warning: Expecting numeric in N722 / R722C14: got 'NA'
## Warning: Expecting numeric in O722 / R722C15: got 'NA'
## Warning: Expecting numeric in R722 / R722C18: got 'NA'
## Warning: Expecting numeric in S722 / R722C19: got 'NA'
## Warning: Expecting numeric in T722 / R722C20: got 'NA'
## Warning: Expecting numeric in M723 / R723C13: got 'NA'
## Warning: Expecting numeric in N723 / R723C14: got 'NA'
## Warning: Expecting numeric in O723 / R723C15: got 'NA'
## Warning: Expecting numeric in R723 / R723C18: got 'NA'
## Warning: Expecting numeric in S723 / R723C19: got 'NA'
## Warning: Expecting numeric in T723 / R723C20: got 'NA'
## Warning: Expecting numeric in M724 / R724C13: got 'NA'
## Warning: Expecting numeric in N724 / R724C14: got 'NA'
## Warning: Expecting numeric in O724 / R724C15: got 'NA'
## Warning: Expecting numeric in R724 / R724C18: got 'NA'
## Warning: Expecting numeric in S724 / R724C19: got 'NA'
## Warning: Expecting numeric in T724 / R724C20: got 'NA'
## Warning: Expecting numeric in M725 / R725C13: got 'NA'
## Warning: Expecting numeric in N725 / R725C14: got 'NA'
## Warning: Expecting numeric in O725 / R725C15: got 'NA'
## Warning: Expecting numeric in R725 / R725C18: got 'NA'
## Warning: Expecting numeric in S725 / R725C19: got 'NA'
## Warning: Expecting numeric in T725 / R725C20: got 'NA'
## Warning: Expecting numeric in M726 / R726C13: got 'NA'
## Warning: Expecting numeric in N726 / R726C14: got 'NA'
## Warning: Expecting numeric in O726 / R726C15: got 'NA'
## Warning: Expecting numeric in R726 / R726C18: got 'NA'
## Warning: Expecting numeric in S726 / R726C19: got 'NA'
## Warning: Expecting numeric in T726 / R726C20: got 'NA'
## Warning: Expecting numeric in M727 / R727C13: got 'NA'
## Warning: Expecting numeric in N727 / R727C14: got 'NA'
## Warning: Expecting numeric in O727 / R727C15: got 'NA'
## Warning: Expecting numeric in R727 / R727C18: got 'NA'
## Warning: Expecting numeric in S727 / R727C19: got 'NA'
## Warning: Expecting numeric in T727 / R727C20: got 'NA'
## Warning: Expecting numeric in M728 / R728C13: got 'NA'
## Warning: Expecting numeric in N728 / R728C14: got 'NA'
## Warning: Expecting numeric in O728 / R728C15: got 'NA'
## Warning: Expecting numeric in R728 / R728C18: got 'NA'
## Warning: Expecting numeric in S728 / R728C19: got 'NA'
## Warning: Expecting numeric in T728 / R728C20: got 'NA'
## Warning: Expecting numeric in M729 / R729C13: got 'NA'
## Warning: Expecting numeric in N729 / R729C14: got 'NA'
## Warning: Expecting numeric in O729 / R729C15: got 'NA'
## Warning: Expecting numeric in R729 / R729C18: got 'NA'
## Warning: Expecting numeric in S729 / R729C19: got 'NA'
## Warning: Expecting numeric in T729 / R729C20: got 'NA'
## Warning: Expecting numeric in M730 / R730C13: got 'NA'
## Warning: Expecting numeric in N730 / R730C14: got 'NA'
## Warning: Expecting numeric in O730 / R730C15: got 'NA'
## Warning: Expecting numeric in R730 / R730C18: got 'NA'
## Warning: Expecting numeric in S730 / R730C19: got 'NA'
## Warning: Expecting numeric in T730 / R730C20: got 'NA'
## Warning: Expecting numeric in M731 / R731C13: got 'NA'
## Warning: Expecting numeric in N731 / R731C14: got 'NA'
## Warning: Expecting numeric in O731 / R731C15: got 'NA'
## Warning: Expecting numeric in R731 / R731C18: got 'NA'
## Warning: Expecting numeric in S731 / R731C19: got 'NA'
## Warning: Expecting numeric in T731 / R731C20: got 'NA'
## Warning: Expecting numeric in M732 / R732C13: got 'NA'
## Warning: Expecting numeric in N732 / R732C14: got 'NA'
## Warning: Expecting numeric in O732 / R732C15: got 'NA'
## Warning: Expecting numeric in R732 / R732C18: got 'NA'
## Warning: Expecting numeric in S732 / R732C19: got 'NA'
## Warning: Expecting numeric in T732 / R732C20: got 'NA'
## Warning: Expecting numeric in M733 / R733C13: got 'NA'
## Warning: Expecting numeric in N733 / R733C14: got 'NA'
## Warning: Expecting numeric in O733 / R733C15: got 'NA'
## Warning: Expecting numeric in R733 / R733C18: got 'NA'
## Warning: Expecting numeric in S733 / R733C19: got 'NA'
## Warning: Expecting numeric in T733 / R733C20: got 'NA'
## Warning: Expecting numeric in M734 / R734C13: got 'NA'
## Warning: Expecting numeric in N734 / R734C14: got 'NA'
## Warning: Expecting numeric in O734 / R734C15: got 'NA'
## Warning: Expecting numeric in R734 / R734C18: got 'NA'
## Warning: Expecting numeric in S734 / R734C19: got 'NA'
## Warning: Expecting numeric in T734 / R734C20: got 'NA'
## Warning: Expecting numeric in M735 / R735C13: got 'NA'
## Warning: Expecting numeric in N735 / R735C14: got 'NA'
## Warning: Expecting numeric in O735 / R735C15: got 'NA'
## Warning: Expecting numeric in R735 / R735C18: got 'NA'
## Warning: Expecting numeric in S735 / R735C19: got 'NA'
## Warning: Expecting numeric in T735 / R735C20: got 'NA'
## Warning: Expecting numeric in M736 / R736C13: got 'NA'
## Warning: Expecting numeric in N736 / R736C14: got 'NA'
## Warning: Expecting numeric in O736 / R736C15: got 'NA'
## Warning: Expecting numeric in R736 / R736C18: got 'NA'
## Warning: Expecting numeric in S736 / R736C19: got 'NA'
## Warning: Expecting numeric in T736 / R736C20: got 'NA'
## Warning: Expecting numeric in M737 / R737C13: got 'NA'
## Warning: Expecting numeric in N737 / R737C14: got 'NA'
## Warning: Expecting numeric in O737 / R737C15: got 'NA'
## Warning: Expecting numeric in R737 / R737C18: got 'NA'
## Warning: Expecting numeric in S737 / R737C19: got 'NA'
## Warning: Expecting numeric in T737 / R737C20: got 'NA'
## Warning: Expecting numeric in M738 / R738C13: got 'NA'
## Warning: Expecting numeric in N738 / R738C14: got 'NA'
## Warning: Expecting numeric in O738 / R738C15: got 'NA'
## Warning: Expecting numeric in R738 / R738C18: got 'NA'
## Warning: Expecting numeric in S738 / R738C19: got 'NA'
## Warning: Expecting numeric in T738 / R738C20: got 'NA'
## Warning: Expecting numeric in M739 / R739C13: got 'NA'
## Warning: Expecting numeric in N739 / R739C14: got 'NA'
## Warning: Expecting numeric in O739 / R739C15: got 'NA'
## Warning: Expecting numeric in R739 / R739C18: got 'NA'
## Warning: Expecting numeric in S739 / R739C19: got 'NA'
## Warning: Expecting numeric in T739 / R739C20: got 'NA'
## Warning: Expecting numeric in M740 / R740C13: got 'NA'
## Warning: Expecting numeric in N740 / R740C14: got 'NA'
## Warning: Expecting numeric in O740 / R740C15: got 'NA'
## Warning: Expecting numeric in R740 / R740C18: got 'NA'
## Warning: Expecting numeric in S740 / R740C19: got 'NA'
## Warning: Expecting numeric in T740 / R740C20: got 'NA'
## Warning: Expecting numeric in M741 / R741C13: got 'NA'
## Warning: Expecting numeric in N741 / R741C14: got 'NA'
## Warning: Expecting numeric in O741 / R741C15: got 'NA'
## Warning: Expecting numeric in R741 / R741C18: got 'NA'
## Warning: Expecting numeric in S741 / R741C19: got 'NA'
## Warning: Expecting numeric in T741 / R741C20: got 'NA'
## Warning: Expecting numeric in M742 / R742C13: got 'NA'
## Warning: Expecting numeric in N742 / R742C14: got 'NA'
## Warning: Expecting numeric in O742 / R742C15: got 'NA'
## Warning: Expecting numeric in R742 / R742C18: got 'NA'
## Warning: Expecting numeric in S742 / R742C19: got 'NA'
## Warning: Expecting numeric in T742 / R742C20: got 'NA'
## Warning: Expecting numeric in M743 / R743C13: got 'NA'
## Warning: Expecting numeric in N743 / R743C14: got 'NA'
## Warning: Expecting numeric in O743 / R743C15: got 'NA'
## Warning: Expecting numeric in R743 / R743C18: got 'NA'
## Warning: Expecting numeric in S743 / R743C19: got 'NA'
## Warning: Expecting numeric in T743 / R743C20: got 'NA'
## Warning: Expecting numeric in M744 / R744C13: got 'NA'
## Warning: Expecting numeric in N744 / R744C14: got 'NA'
## Warning: Expecting numeric in O744 / R744C15: got 'NA'
## Warning: Expecting numeric in R744 / R744C18: got 'NA'
## Warning: Expecting numeric in S744 / R744C19: got 'NA'
## Warning: Expecting numeric in T744 / R744C20: got 'NA'
## Warning: Expecting numeric in M745 / R745C13: got 'NA'
## Warning: Expecting numeric in N745 / R745C14: got 'NA'
## Warning: Expecting numeric in O745 / R745C15: got 'NA'
## Warning: Expecting numeric in R745 / R745C18: got 'NA'
## Warning: Expecting numeric in S745 / R745C19: got 'NA'
## Warning: Expecting numeric in T745 / R745C20: got 'NA'
## Warning: Expecting numeric in M746 / R746C13: got 'NA'
## Warning: Expecting numeric in N746 / R746C14: got 'NA'
## Warning: Expecting numeric in O746 / R746C15: got 'NA'
## Warning: Expecting numeric in R746 / R746C18: got 'NA'
## Warning: Expecting numeric in S746 / R746C19: got 'NA'
## Warning: Expecting numeric in T746 / R746C20: got 'NA'
## Warning: Expecting numeric in M747 / R747C13: got 'NA'
## Warning: Expecting numeric in N747 / R747C14: got 'NA'
## Warning: Expecting numeric in O747 / R747C15: got 'NA'
## Warning: Expecting numeric in R747 / R747C18: got 'NA'
## Warning: Expecting numeric in S747 / R747C19: got 'NA'
## Warning: Expecting numeric in T747 / R747C20: got 'NA'
## Warning: Expecting numeric in M748 / R748C13: got 'NA'
## Warning: Expecting numeric in N748 / R748C14: got 'NA'
## Warning: Expecting numeric in O748 / R748C15: got 'NA'
## Warning: Expecting numeric in R748 / R748C18: got 'NA'
## Warning: Expecting numeric in S748 / R748C19: got 'NA'
## Warning: Expecting numeric in T748 / R748C20: got 'NA'
## Warning: Expecting numeric in M749 / R749C13: got 'NA'
## Warning: Expecting numeric in N749 / R749C14: got 'NA'
## Warning: Expecting numeric in O749 / R749C15: got 'NA'
## Warning: Expecting numeric in R749 / R749C18: got 'NA'
## Warning: Expecting numeric in S749 / R749C19: got 'NA'
## Warning: Expecting numeric in T749 / R749C20: got 'NA'
## Warning: Expecting numeric in M750 / R750C13: got 'NA'
## Warning: Expecting numeric in N750 / R750C14: got 'NA'
## Warning: Expecting numeric in O750 / R750C15: got 'NA'
## Warning: Expecting numeric in R750 / R750C18: got 'NA'
## Warning: Expecting numeric in S750 / R750C19: got 'NA'
## Warning: Expecting numeric in T750 / R750C20: got 'NA'
## Warning: Expecting numeric in M751 / R751C13: got 'NA'
## Warning: Expecting numeric in N751 / R751C14: got 'NA'
## Warning: Expecting numeric in O751 / R751C15: got 'NA'
## Warning: Expecting numeric in R751 / R751C18: got 'NA'
## Warning: Expecting numeric in S751 / R751C19: got 'NA'
## Warning: Expecting numeric in T751 / R751C20: got 'NA'
## Warning: Expecting numeric in M752 / R752C13: got 'NA'
## Warning: Expecting numeric in N752 / R752C14: got 'NA'
## Warning: Expecting numeric in O752 / R752C15: got 'NA'
## Warning: Expecting numeric in R752 / R752C18: got 'NA'
## Warning: Expecting numeric in S752 / R752C19: got 'NA'
## Warning: Expecting numeric in T752 / R752C20: got 'NA'
## Warning: Expecting numeric in M753 / R753C13: got 'NA'
## Warning: Expecting numeric in N753 / R753C14: got 'NA'
## Warning: Expecting numeric in O753 / R753C15: got 'NA'
## Warning: Expecting numeric in R753 / R753C18: got 'NA'
## Warning: Expecting numeric in S753 / R753C19: got 'NA'
## Warning: Expecting numeric in T753 / R753C20: got 'NA'
## Warning: Expecting numeric in M754 / R754C13: got 'NA'
## Warning: Expecting numeric in N754 / R754C14: got 'NA'
## Warning: Expecting numeric in O754 / R754C15: got 'NA'
## Warning: Expecting numeric in R754 / R754C18: got 'NA'
## Warning: Expecting numeric in S754 / R754C19: got 'NA'
## Warning: Expecting numeric in T754 / R754C20: got 'NA'
## Warning: Expecting numeric in M755 / R755C13: got 'NA'
## Warning: Expecting numeric in N755 / R755C14: got 'NA'
## Warning: Expecting numeric in O755 / R755C15: got 'NA'
## Warning: Expecting numeric in R755 / R755C18: got 'NA'
## Warning: Expecting numeric in S755 / R755C19: got 'NA'
## Warning: Expecting numeric in T755 / R755C20: got 'NA'
## Warning: Expecting numeric in M756 / R756C13: got 'NA'
## Warning: Expecting numeric in N756 / R756C14: got 'NA'
## Warning: Expecting numeric in O756 / R756C15: got 'NA'
## Warning: Expecting numeric in R756 / R756C18: got 'NA'
## Warning: Expecting numeric in S756 / R756C19: got 'NA'
## Warning: Expecting numeric in T756 / R756C20: got 'NA'
## Warning: Expecting numeric in M757 / R757C13: got 'NA'
## Warning: Expecting numeric in N757 / R757C14: got 'NA'
## Warning: Expecting numeric in O757 / R757C15: got 'NA'
## Warning: Expecting numeric in R757 / R757C18: got 'NA'
## Warning: Expecting numeric in S757 / R757C19: got 'NA'
## Warning: Expecting numeric in T757 / R757C20: got 'NA'
## Warning: Expecting numeric in M758 / R758C13: got 'NA'
## Warning: Expecting numeric in N758 / R758C14: got 'NA'
## Warning: Expecting numeric in O758 / R758C15: got 'NA'
## Warning: Expecting numeric in R758 / R758C18: got 'NA'
## Warning: Expecting numeric in S758 / R758C19: got 'NA'
## Warning: Expecting numeric in T758 / R758C20: got 'NA'
## Warning: Expecting numeric in M759 / R759C13: got 'NA'
## Warning: Expecting numeric in N759 / R759C14: got 'NA'
## Warning: Expecting numeric in O759 / R759C15: got 'NA'
## Warning: Expecting numeric in R759 / R759C18: got 'NA'
## Warning: Expecting numeric in S759 / R759C19: got 'NA'
## Warning: Expecting numeric in T759 / R759C20: got 'NA'
## Warning: Expecting numeric in M760 / R760C13: got 'NA'
## Warning: Expecting numeric in N760 / R760C14: got 'NA'
## Warning: Expecting numeric in O760 / R760C15: got 'NA'
## Warning: Expecting numeric in R760 / R760C18: got 'NA'
## Warning: Expecting numeric in S760 / R760C19: got 'NA'
## Warning: Expecting numeric in T760 / R760C20: got 'NA'
## Warning: Expecting numeric in M761 / R761C13: got 'NA'
## Warning: Expecting numeric in N761 / R761C14: got 'NA'
## Warning: Expecting numeric in O761 / R761C15: got 'NA'
## Warning: Expecting numeric in R761 / R761C18: got 'NA'
## Warning: Expecting numeric in S761 / R761C19: got 'NA'
## Warning: Expecting numeric in T761 / R761C20: got 'NA'
## Warning: Expecting numeric in M762 / R762C13: got 'NA'
## Warning: Expecting numeric in N762 / R762C14: got 'NA'
## Warning: Expecting numeric in O762 / R762C15: got 'NA'
## Warning: Expecting numeric in R762 / R762C18: got 'NA'
## Warning: Expecting numeric in S762 / R762C19: got 'NA'
## Warning: Expecting numeric in T762 / R762C20: got 'NA'
## Warning: Expecting numeric in M763 / R763C13: got 'NA'
## Warning: Expecting numeric in N763 / R763C14: got 'NA'
## Warning: Expecting numeric in O763 / R763C15: got 'NA'
## Warning: Expecting numeric in R763 / R763C18: got 'NA'
## Warning: Expecting numeric in S763 / R763C19: got 'NA'
## Warning: Expecting numeric in T763 / R763C20: got 'NA'
## Warning: Expecting numeric in M764 / R764C13: got 'NA'
## Warning: Expecting numeric in N764 / R764C14: got 'NA'
## Warning: Expecting numeric in O764 / R764C15: got 'NA'
## Warning: Expecting numeric in R764 / R764C18: got 'NA'
## Warning: Expecting numeric in S764 / R764C19: got 'NA'
## Warning: Expecting numeric in T764 / R764C20: got 'NA'
## Warning: Expecting numeric in M765 / R765C13: got 'NA'
## Warning: Expecting numeric in N765 / R765C14: got 'NA'
## Warning: Expecting numeric in O765 / R765C15: got 'NA'
## Warning: Expecting numeric in R765 / R765C18: got 'NA'
## Warning: Expecting numeric in S765 / R765C19: got 'NA'
## Warning: Expecting numeric in T765 / R765C20: got 'NA'
## Warning: Expecting numeric in M766 / R766C13: got 'NA'
## Warning: Expecting numeric in N766 / R766C14: got 'NA'
## Warning: Expecting numeric in O766 / R766C15: got 'NA'
## Warning: Expecting numeric in R766 / R766C18: got 'NA'
## Warning: Expecting numeric in S766 / R766C19: got 'NA'
## Warning: Expecting numeric in T766 / R766C20: got 'NA'
## Warning: Expecting numeric in M767 / R767C13: got 'NA'
## Warning: Expecting numeric in N767 / R767C14: got 'NA'
## Warning: Expecting numeric in O767 / R767C15: got 'NA'
## Warning: Expecting numeric in R767 / R767C18: got 'NA'
## Warning: Expecting numeric in S767 / R767C19: got 'NA'
## Warning: Expecting numeric in T767 / R767C20: got 'NA'
## Warning: Expecting numeric in M768 / R768C13: got 'NA'
## Warning: Expecting numeric in N768 / R768C14: got 'NA'
## Warning: Expecting numeric in O768 / R768C15: got 'NA'
## Warning: Expecting numeric in R768 / R768C18: got 'NA'
## Warning: Expecting numeric in S768 / R768C19: got 'NA'
## Warning: Expecting numeric in T768 / R768C20: got 'NA'
## Warning: Expecting numeric in M769 / R769C13: got 'NA'
## Warning: Expecting numeric in N769 / R769C14: got 'NA'
## Warning: Expecting numeric in O769 / R769C15: got 'NA'
## Warning: Expecting numeric in R769 / R769C18: got 'NA'
## Warning: Expecting numeric in S769 / R769C19: got 'NA'
## Warning: Expecting numeric in T769 / R769C20: got 'NA'
## Warning: Expecting numeric in M770 / R770C13: got 'NA'
## Warning: Expecting numeric in N770 / R770C14: got 'NA'
## Warning: Expecting numeric in O770 / R770C15: got 'NA'
## Warning: Expecting numeric in R770 / R770C18: got 'NA'
## Warning: Expecting numeric in S770 / R770C19: got 'NA'
## Warning: Expecting numeric in T770 / R770C20: got 'NA'
## Warning: Expecting numeric in M771 / R771C13: got 'NA'
## Warning: Expecting numeric in N771 / R771C14: got 'NA'
## Warning: Expecting numeric in O771 / R771C15: got 'NA'
## Warning: Expecting numeric in R771 / R771C18: got 'NA'
## Warning: Expecting numeric in S771 / R771C19: got 'NA'
## Warning: Expecting numeric in T771 / R771C20: got 'NA'
## Warning: Expecting numeric in M772 / R772C13: got 'NA'
## Warning: Expecting numeric in N772 / R772C14: got 'NA'
## Warning: Expecting numeric in O772 / R772C15: got 'NA'
## Warning: Expecting numeric in R772 / R772C18: got 'NA'
## Warning: Expecting numeric in S772 / R772C19: got 'NA'
## Warning: Expecting numeric in T772 / R772C20: got 'NA'
## Warning: Expecting numeric in M773 / R773C13: got 'NA'
## Warning: Expecting numeric in N773 / R773C14: got 'NA'
## Warning: Expecting numeric in O773 / R773C15: got 'NA'
## Warning: Expecting numeric in R773 / R773C18: got 'NA'
## Warning: Expecting numeric in S773 / R773C19: got 'NA'
## Warning: Expecting numeric in T773 / R773C20: got 'NA'
## Warning: Expecting numeric in M774 / R774C13: got 'NA'
## Warning: Expecting numeric in N774 / R774C14: got 'NA'
## Warning: Expecting numeric in O774 / R774C15: got 'NA'
## Warning: Expecting numeric in R774 / R774C18: got 'NA'
## Warning: Expecting numeric in S774 / R774C19: got 'NA'
## Warning: Expecting numeric in T774 / R774C20: got 'NA'
## Warning: Expecting numeric in M775 / R775C13: got 'NA'
## Warning: Expecting numeric in N775 / R775C14: got 'NA'
## Warning: Expecting numeric in O775 / R775C15: got 'NA'
## Warning: Expecting numeric in R775 / R775C18: got 'NA'
## Warning: Expecting numeric in S775 / R775C19: got 'NA'
## Warning: Expecting numeric in T775 / R775C20: got 'NA'
## Warning: Expecting numeric in M776 / R776C13: got 'NA'
## Warning: Expecting numeric in N776 / R776C14: got 'NA'
## Warning: Expecting numeric in O776 / R776C15: got 'NA'
## Warning: Expecting numeric in R776 / R776C18: got 'NA'
## Warning: Expecting numeric in S776 / R776C19: got 'NA'
## Warning: Expecting numeric in T776 / R776C20: got 'NA'
## Warning: Expecting numeric in M777 / R777C13: got 'NA'
## Warning: Expecting numeric in N777 / R777C14: got 'NA'
## Warning: Expecting numeric in O777 / R777C15: got 'NA'
## Warning: Expecting numeric in R777 / R777C18: got 'NA'
## Warning: Expecting numeric in S777 / R777C19: got 'NA'
## Warning: Expecting numeric in T777 / R777C20: got 'NA'
## Warning: Expecting numeric in M778 / R778C13: got 'NA'
## Warning: Expecting numeric in N778 / R778C14: got 'NA'
## Warning: Expecting numeric in O778 / R778C15: got 'NA'
## Warning: Expecting numeric in R778 / R778C18: got 'NA'
## Warning: Expecting numeric in S778 / R778C19: got 'NA'
## Warning: Expecting numeric in T778 / R778C20: got 'NA'
## Warning: Expecting numeric in M779 / R779C13: got 'NA'
## Warning: Expecting numeric in N779 / R779C14: got 'NA'
## Warning: Expecting numeric in O779 / R779C15: got 'NA'
## Warning: Expecting numeric in R779 / R779C18: got 'NA'
## Warning: Expecting numeric in S779 / R779C19: got 'NA'
## Warning: Expecting numeric in T779 / R779C20: got 'NA'
## Warning: Expecting numeric in M780 / R780C13: got 'NA'
## Warning: Expecting numeric in N780 / R780C14: got 'NA'
## Warning: Expecting numeric in O780 / R780C15: got 'NA'
## Warning: Expecting numeric in R780 / R780C18: got 'NA'
## Warning: Expecting numeric in S780 / R780C19: got 'NA'
## Warning: Expecting numeric in T780 / R780C20: got 'NA'
## Warning: Expecting numeric in M781 / R781C13: got 'NA'
## Warning: Expecting numeric in N781 / R781C14: got 'NA'
## Warning: Expecting numeric in O781 / R781C15: got 'NA'
## Warning: Expecting numeric in R781 / R781C18: got 'NA'
## Warning: Expecting numeric in S781 / R781C19: got 'NA'
## Warning: Expecting numeric in T781 / R781C20: got 'NA'
## Warning: Expecting numeric in M782 / R782C13: got 'NA'
## Warning: Expecting numeric in N782 / R782C14: got 'NA'
## Warning: Expecting numeric in O782 / R782C15: got 'NA'
## Warning: Expecting numeric in R782 / R782C18: got 'NA'
## Warning: Expecting numeric in S782 / R782C19: got 'NA'
## Warning: Expecting numeric in T782 / R782C20: got 'NA'
## Warning: Expecting numeric in M783 / R783C13: got 'NA'
## Warning: Expecting numeric in N783 / R783C14: got 'NA'
## Warning: Expecting numeric in O783 / R783C15: got 'NA'
## Warning: Expecting numeric in R783 / R783C18: got 'NA'
## Warning: Expecting numeric in S783 / R783C19: got 'NA'
## Warning: Expecting numeric in T783 / R783C20: got 'NA'
## Warning: Expecting numeric in M784 / R784C13: got 'NA'
## Warning: Expecting numeric in N784 / R784C14: got 'NA'
## Warning: Expecting numeric in O784 / R784C15: got 'NA'
## Warning: Expecting numeric in R784 / R784C18: got 'NA'
## Warning: Expecting numeric in S784 / R784C19: got 'NA'
## Warning: Expecting numeric in T784 / R784C20: got 'NA'
## Warning: Expecting numeric in M785 / R785C13: got 'NA'
## Warning: Expecting numeric in N785 / R785C14: got 'NA'
## Warning: Expecting numeric in O785 / R785C15: got 'NA'
## Warning: Expecting numeric in R785 / R785C18: got 'NA'
## Warning: Expecting numeric in S785 / R785C19: got 'NA'
## Warning: Expecting numeric in T785 / R785C20: got 'NA'
## Warning: Expecting numeric in M786 / R786C13: got 'NA'
## Warning: Expecting numeric in N786 / R786C14: got 'NA'
## Warning: Expecting numeric in O786 / R786C15: got 'NA'
## Warning: Expecting numeric in R786 / R786C18: got 'NA'
## Warning: Expecting numeric in S786 / R786C19: got 'NA'
## Warning: Expecting numeric in T786 / R786C20: got 'NA'
## Warning: Expecting numeric in M787 / R787C13: got 'NA'
## Warning: Expecting numeric in N787 / R787C14: got 'NA'
## Warning: Expecting numeric in O787 / R787C15: got 'NA'
## Warning: Expecting numeric in R787 / R787C18: got 'NA'
## Warning: Expecting numeric in S787 / R787C19: got 'NA'
## Warning: Expecting numeric in T787 / R787C20: got 'NA'
## Warning: Expecting numeric in M788 / R788C13: got 'NA'
## Warning: Expecting numeric in N788 / R788C14: got 'NA'
## Warning: Expecting numeric in O788 / R788C15: got 'NA'
## Warning: Expecting numeric in R788 / R788C18: got 'NA'
## Warning: Expecting numeric in S788 / R788C19: got 'NA'
## Warning: Expecting numeric in T788 / R788C20: got 'NA'
## Warning: Expecting numeric in M789 / R789C13: got 'NA'
## Warning: Expecting numeric in N789 / R789C14: got 'NA'
## Warning: Expecting numeric in O789 / R789C15: got 'NA'
## Warning: Expecting numeric in R789 / R789C18: got 'NA'
## Warning: Expecting numeric in S789 / R789C19: got 'NA'
## Warning: Expecting numeric in T789 / R789C20: got 'NA'
## Warning: Expecting numeric in M790 / R790C13: got 'NA'
## Warning: Expecting numeric in N790 / R790C14: got 'NA'
## Warning: Expecting numeric in O790 / R790C15: got 'NA'
## Warning: Expecting numeric in R790 / R790C18: got 'NA'
## Warning: Expecting numeric in S790 / R790C19: got 'NA'
## Warning: Expecting numeric in T790 / R790C20: got 'NA'
## Warning: Expecting numeric in M791 / R791C13: got 'NA'
## Warning: Expecting numeric in N791 / R791C14: got 'NA'
## Warning: Expecting numeric in O791 / R791C15: got 'NA'
## Warning: Expecting numeric in R791 / R791C18: got 'NA'
## Warning: Expecting numeric in S791 / R791C19: got 'NA'
## Warning: Expecting numeric in T791 / R791C20: got 'NA'
## Warning: Expecting numeric in M792 / R792C13: got 'NA'
## Warning: Expecting numeric in N792 / R792C14: got 'NA'
## Warning: Expecting numeric in O792 / R792C15: got 'NA'
## Warning: Expecting numeric in R792 / R792C18: got 'NA'
## Warning: Expecting numeric in S792 / R792C19: got 'NA'
## Warning: Expecting numeric in T792 / R792C20: got 'NA'
## Warning: Expecting numeric in M793 / R793C13: got 'NA'
## Warning: Expecting numeric in N793 / R793C14: got 'NA'
## Warning: Expecting numeric in O793 / R793C15: got 'NA'
## Warning: Expecting numeric in R793 / R793C18: got 'NA'
## Warning: Expecting numeric in S793 / R793C19: got 'NA'
## Warning: Expecting numeric in T793 / R793C20: got 'NA'
## Warning: Expecting numeric in M794 / R794C13: got 'NA'
## Warning: Expecting numeric in N794 / R794C14: got 'NA'
## Warning: Expecting numeric in O794 / R794C15: got 'NA'
## Warning: Expecting numeric in R794 / R794C18: got 'NA'
## Warning: Expecting numeric in S794 / R794C19: got 'NA'
## Warning: Expecting numeric in T794 / R794C20: got 'NA'
## Warning: Expecting numeric in M795 / R795C13: got 'NA'
## Warning: Expecting numeric in N795 / R795C14: got 'NA'
## Warning: Expecting numeric in O795 / R795C15: got 'NA'
## Warning: Expecting numeric in R795 / R795C18: got 'NA'
## Warning: Expecting numeric in S795 / R795C19: got 'NA'
## Warning: Expecting numeric in T795 / R795C20: got 'NA'
## Warning: Expecting numeric in M796 / R796C13: got 'NA'
## Warning: Expecting numeric in N796 / R796C14: got 'NA'
## Warning: Expecting numeric in O796 / R796C15: got 'NA'
## Warning: Expecting numeric in R796 / R796C18: got 'NA'
## Warning: Expecting numeric in S796 / R796C19: got 'NA'
## Warning: Expecting numeric in T796 / R796C20: got 'NA'
## Warning: Expecting numeric in M797 / R797C13: got 'NA'
## Warning: Expecting numeric in N797 / R797C14: got 'NA'
## Warning: Expecting numeric in O797 / R797C15: got 'NA'
## Warning: Expecting numeric in R797 / R797C18: got 'NA'
## Warning: Expecting numeric in S797 / R797C19: got 'NA'
## Warning: Expecting numeric in T797 / R797C20: got 'NA'
## Warning: Expecting numeric in M798 / R798C13: got 'NA'
## Warning: Expecting numeric in N798 / R798C14: got 'NA'
## Warning: Expecting numeric in O798 / R798C15: got 'NA'
## Warning: Expecting numeric in R798 / R798C18: got 'NA'
## Warning: Expecting numeric in S798 / R798C19: got 'NA'
## Warning: Expecting numeric in T798 / R798C20: got 'NA'
## Warning: Expecting numeric in M799 / R799C13: got 'NA'
## Warning: Expecting numeric in N799 / R799C14: got 'NA'
## Warning: Expecting numeric in O799 / R799C15: got 'NA'
## Warning: Expecting numeric in R799 / R799C18: got 'NA'
## Warning: Expecting numeric in S799 / R799C19: got 'NA'
## Warning: Expecting numeric in T799 / R799C20: got 'NA'
## Warning: Expecting numeric in M800 / R800C13: got 'NA'
## Warning: Expecting numeric in N800 / R800C14: got 'NA'
## Warning: Expecting numeric in O800 / R800C15: got 'NA'
## Warning: Expecting numeric in R800 / R800C18: got 'NA'
## Warning: Expecting numeric in S800 / R800C19: got 'NA'
## Warning: Expecting numeric in T800 / R800C20: got 'NA'
## Warning: Expecting numeric in M801 / R801C13: got 'NA'
## Warning: Expecting numeric in N801 / R801C14: got 'NA'
## Warning: Expecting numeric in O801 / R801C15: got 'NA'
## Warning: Expecting numeric in R801 / R801C18: got 'NA'
## Warning: Expecting numeric in S801 / R801C19: got 'NA'
## Warning: Expecting numeric in T801 / R801C20: got 'NA'
## Warning: Expecting numeric in M802 / R802C13: got 'NA'
## Warning: Expecting numeric in N802 / R802C14: got 'NA'
## Warning: Expecting numeric in O802 / R802C15: got 'NA'
## Warning: Expecting numeric in R802 / R802C18: got 'NA'
## Warning: Expecting numeric in S802 / R802C19: got 'NA'
## Warning: Expecting numeric in T802 / R802C20: got 'NA'
## Warning: Expecting numeric in M803 / R803C13: got 'NA'
## Warning: Expecting numeric in N803 / R803C14: got 'NA'
## Warning: Expecting numeric in O803 / R803C15: got 'NA'
## Warning: Expecting numeric in R803 / R803C18: got 'NA'
## Warning: Expecting numeric in S803 / R803C19: got 'NA'
## Warning: Expecting numeric in T803 / R803C20: got 'NA'
## Warning: Expecting numeric in M804 / R804C13: got 'NA'
## Warning: Expecting numeric in N804 / R804C14: got 'NA'
## Warning: Expecting numeric in O804 / R804C15: got 'NA'
## Warning: Expecting numeric in R804 / R804C18: got 'NA'
## Warning: Expecting numeric in S804 / R804C19: got 'NA'
## Warning: Expecting numeric in T804 / R804C20: got 'NA'
## Warning: Expecting numeric in M805 / R805C13: got 'NA'
## Warning: Expecting numeric in N805 / R805C14: got 'NA'
## Warning: Expecting numeric in O805 / R805C15: got 'NA'
## Warning: Expecting numeric in R805 / R805C18: got 'NA'
## Warning: Expecting numeric in S805 / R805C19: got 'NA'
## Warning: Expecting numeric in T805 / R805C20: got 'NA'
## Warning: Expecting numeric in M806 / R806C13: got 'NA'
## Warning: Expecting numeric in N806 / R806C14: got 'NA'
## Warning: Expecting numeric in O806 / R806C15: got 'NA'
## Warning: Expecting numeric in R806 / R806C18: got 'NA'
## Warning: Expecting numeric in S806 / R806C19: got 'NA'
## Warning: Expecting numeric in T806 / R806C20: got 'NA'
## Warning: Expecting numeric in M807 / R807C13: got 'NA'
## Warning: Expecting numeric in N807 / R807C14: got 'NA'
## Warning: Expecting numeric in O807 / R807C15: got 'NA'
## Warning: Expecting numeric in R807 / R807C18: got 'NA'
## Warning: Expecting numeric in S807 / R807C19: got 'NA'
## Warning: Expecting numeric in T807 / R807C20: got 'NA'
## Warning: Expecting numeric in M808 / R808C13: got 'NA'
## Warning: Expecting numeric in N808 / R808C14: got 'NA'
## Warning: Expecting numeric in O808 / R808C15: got 'NA'
## Warning: Expecting numeric in R808 / R808C18: got 'NA'
## Warning: Expecting numeric in S808 / R808C19: got 'NA'
## Warning: Expecting numeric in T808 / R808C20: got 'NA'
## Warning: Expecting numeric in M809 / R809C13: got 'NA'
## Warning: Expecting numeric in N809 / R809C14: got 'NA'
## Warning: Expecting numeric in O809 / R809C15: got 'NA'
## Warning: Expecting numeric in R809 / R809C18: got 'NA'
## Warning: Expecting numeric in S809 / R809C19: got 'NA'
## Warning: Expecting numeric in T809 / R809C20: got 'NA'
## Warning: Expecting numeric in M810 / R810C13: got 'NA'
## Warning: Expecting numeric in N810 / R810C14: got 'NA'
## Warning: Expecting numeric in O810 / R810C15: got 'NA'
## Warning: Expecting numeric in R810 / R810C18: got 'NA'
## Warning: Expecting numeric in S810 / R810C19: got 'NA'
## Warning: Expecting numeric in T810 / R810C20: got 'NA'
## Warning: Expecting numeric in M811 / R811C13: got 'NA'
## Warning: Expecting numeric in N811 / R811C14: got 'NA'
## Warning: Expecting numeric in O811 / R811C15: got 'NA'
## Warning: Expecting numeric in R811 / R811C18: got 'NA'
## Warning: Expecting numeric in S811 / R811C19: got 'NA'
## Warning: Expecting numeric in T811 / R811C20: got 'NA'
## Warning: Expecting numeric in M812 / R812C13: got 'NA'
## Warning: Expecting numeric in N812 / R812C14: got 'NA'
## Warning: Expecting numeric in O812 / R812C15: got 'NA'
## Warning: Expecting numeric in R812 / R812C18: got 'NA'
## Warning: Expecting numeric in S812 / R812C19: got 'NA'
## Warning: Expecting numeric in T812 / R812C20: got 'NA'
## Warning: Expecting numeric in M813 / R813C13: got 'NA'
## Warning: Expecting numeric in N813 / R813C14: got 'NA'
## Warning: Expecting numeric in O813 / R813C15: got 'NA'
## Warning: Expecting numeric in R813 / R813C18: got 'NA'
## Warning: Expecting numeric in S813 / R813C19: got 'NA'
## Warning: Expecting numeric in T813 / R813C20: got 'NA'
## Warning: Expecting numeric in M814 / R814C13: got 'NA'
## Warning: Expecting numeric in N814 / R814C14: got 'NA'
## Warning: Expecting numeric in O814 / R814C15: got 'NA'
## Warning: Expecting numeric in R814 / R814C18: got 'NA'
## Warning: Expecting numeric in S814 / R814C19: got 'NA'
## Warning: Expecting numeric in T814 / R814C20: got 'NA'
## Warning: Expecting numeric in M815 / R815C13: got 'NA'
## Warning: Expecting numeric in N815 / R815C14: got 'NA'
## Warning: Expecting numeric in O815 / R815C15: got 'NA'
## Warning: Expecting numeric in R815 / R815C18: got 'NA'
## Warning: Expecting numeric in S815 / R815C19: got 'NA'
## Warning: Expecting numeric in T815 / R815C20: got 'NA'
## Warning: Expecting numeric in M816 / R816C13: got 'NA'
## Warning: Expecting numeric in N816 / R816C14: got 'NA'
## Warning: Expecting numeric in O816 / R816C15: got 'NA'
## Warning: Expecting numeric in R816 / R816C18: got 'NA'
## Warning: Expecting numeric in S816 / R816C19: got 'NA'
## Warning: Expecting numeric in T816 / R816C20: got 'NA'
## Warning: Expecting numeric in M817 / R817C13: got 'NA'
## Warning: Expecting numeric in N817 / R817C14: got 'NA'
## Warning: Expecting numeric in O817 / R817C15: got 'NA'
## Warning: Expecting numeric in R817 / R817C18: got 'NA'
## Warning: Expecting numeric in S817 / R817C19: got 'NA'
## Warning: Expecting numeric in T817 / R817C20: got 'NA'
## Warning: Expecting numeric in M818 / R818C13: got 'NA'
## Warning: Expecting numeric in N818 / R818C14: got 'NA'
## Warning: Expecting numeric in O818 / R818C15: got 'NA'
## Warning: Expecting numeric in R818 / R818C18: got 'NA'
## Warning: Expecting numeric in S818 / R818C19: got 'NA'
## Warning: Expecting numeric in T818 / R818C20: got 'NA'
## Warning: Expecting numeric in M819 / R819C13: got 'NA'
## Warning: Expecting numeric in N819 / R819C14: got 'NA'
## Warning: Expecting numeric in O819 / R819C15: got 'NA'
## Warning: Expecting numeric in R819 / R819C18: got 'NA'
## Warning: Expecting numeric in S819 / R819C19: got 'NA'
## Warning: Expecting numeric in T819 / R819C20: got 'NA'
## Warning: Expecting numeric in M820 / R820C13: got 'NA'
## Warning: Expecting numeric in N820 / R820C14: got 'NA'
## Warning: Expecting numeric in O820 / R820C15: got 'NA'
## Warning: Expecting numeric in R820 / R820C18: got 'NA'
## Warning: Expecting numeric in S820 / R820C19: got 'NA'
## Warning: Expecting numeric in T820 / R820C20: got 'NA'
## Warning: Expecting numeric in M821 / R821C13: got 'NA'
## Warning: Expecting numeric in N821 / R821C14: got 'NA'
## Warning: Expecting numeric in O821 / R821C15: got 'NA'
## Warning: Expecting numeric in R821 / R821C18: got 'NA'
## Warning: Expecting numeric in S821 / R821C19: got 'NA'
## Warning: Expecting numeric in T821 / R821C20: got 'NA'
## Warning: Expecting numeric in M822 / R822C13: got 'NA'
## Warning: Expecting numeric in N822 / R822C14: got 'NA'
## Warning: Expecting numeric in O822 / R822C15: got 'NA'
## Warning: Expecting numeric in R822 / R822C18: got 'NA'
## Warning: Expecting numeric in S822 / R822C19: got 'NA'
## Warning: Expecting numeric in T822 / R822C20: got 'NA'
## Warning: Expecting numeric in M823 / R823C13: got 'NA'
## Warning: Expecting numeric in N823 / R823C14: got 'NA'
## Warning: Expecting numeric in O823 / R823C15: got 'NA'
## Warning: Expecting numeric in R823 / R823C18: got 'NA'
## Warning: Expecting numeric in S823 / R823C19: got 'NA'
## Warning: Expecting numeric in T823 / R823C20: got 'NA'
## Warning: Expecting numeric in M824 / R824C13: got 'NA'
## Warning: Expecting numeric in N824 / R824C14: got 'NA'
## Warning: Expecting numeric in O824 / R824C15: got 'NA'
## Warning: Expecting numeric in R824 / R824C18: got 'NA'
## Warning: Expecting numeric in S824 / R824C19: got 'NA'
## Warning: Expecting numeric in T824 / R824C20: got 'NA'
## Warning: Expecting numeric in M825 / R825C13: got 'NA'
## Warning: Expecting numeric in N825 / R825C14: got 'NA'
## Warning: Expecting numeric in O825 / R825C15: got 'NA'
## Warning: Expecting numeric in R825 / R825C18: got 'NA'
## Warning: Expecting numeric in S825 / R825C19: got 'NA'
## Warning: Expecting numeric in T825 / R825C20: got 'NA'
## Warning: Expecting numeric in M826 / R826C13: got 'NA'
## Warning: Expecting numeric in N826 / R826C14: got 'NA'
## Warning: Expecting numeric in O826 / R826C15: got 'NA'
## Warning: Expecting numeric in R826 / R826C18: got 'NA'
## Warning: Expecting numeric in S826 / R826C19: got 'NA'
## Warning: Expecting numeric in T826 / R826C20: got 'NA'
## Warning: Expecting numeric in M827 / R827C13: got 'NA'
## Warning: Expecting numeric in N827 / R827C14: got 'NA'
## Warning: Expecting numeric in O827 / R827C15: got 'NA'
## Warning: Expecting numeric in R827 / R827C18: got 'NA'
## Warning: Expecting numeric in S827 / R827C19: got 'NA'
## Warning: Expecting numeric in T827 / R827C20: got 'NA'
## Warning: Expecting numeric in M828 / R828C13: got 'NA'
## Warning: Expecting numeric in N828 / R828C14: got 'NA'
## Warning: Expecting numeric in O828 / R828C15: got 'NA'
## Warning: Expecting numeric in R828 / R828C18: got 'NA'
## Warning: Expecting numeric in S828 / R828C19: got 'NA'
## Warning: Expecting numeric in T828 / R828C20: got 'NA'
## Warning: Expecting numeric in M829 / R829C13: got 'NA'
## Warning: Expecting numeric in N829 / R829C14: got 'NA'
## Warning: Expecting numeric in O829 / R829C15: got 'NA'
## Warning: Expecting numeric in R829 / R829C18: got 'NA'
## Warning: Expecting numeric in S829 / R829C19: got 'NA'
## Warning: Expecting numeric in T829 / R829C20: got 'NA'
## Warning: Expecting numeric in M830 / R830C13: got 'NA'
## Warning: Expecting numeric in N830 / R830C14: got 'NA'
## Warning: Expecting numeric in O830 / R830C15: got 'NA'
## Warning: Expecting numeric in R830 / R830C18: got 'NA'
## Warning: Expecting numeric in S830 / R830C19: got 'NA'
## Warning: Expecting numeric in T830 / R830C20: got 'NA'
## Warning: Expecting numeric in M831 / R831C13: got 'NA'
## Warning: Expecting numeric in N831 / R831C14: got 'NA'
## Warning: Expecting numeric in O831 / R831C15: got 'NA'
## Warning: Expecting numeric in R831 / R831C18: got 'NA'
## Warning: Expecting numeric in S831 / R831C19: got 'NA'
## Warning: Expecting numeric in T831 / R831C20: got 'NA'
## Warning: Expecting numeric in M832 / R832C13: got 'NA'
## Warning: Expecting numeric in N832 / R832C14: got 'NA'
## Warning: Expecting numeric in O832 / R832C15: got 'NA'
## Warning: Expecting numeric in R832 / R832C18: got 'NA'
## Warning: Expecting numeric in S832 / R832C19: got 'NA'
## Warning: Expecting numeric in T832 / R832C20: got 'NA'
## Warning: Expecting numeric in M833 / R833C13: got 'NA'
## Warning: Expecting numeric in N833 / R833C14: got 'NA'
## Warning: Expecting numeric in O833 / R833C15: got 'NA'
## Warning: Expecting numeric in R833 / R833C18: got 'NA'
## Warning: Expecting numeric in S833 / R833C19: got 'NA'
## Warning: Expecting numeric in T833 / R833C20: got 'NA'
## Warning: Expecting numeric in M834 / R834C13: got 'NA'
## Warning: Expecting numeric in N834 / R834C14: got 'NA'
## Warning: Expecting numeric in O834 / R834C15: got 'NA'
## Warning: Expecting numeric in R834 / R834C18: got 'NA'
## Warning: Expecting numeric in S834 / R834C19: got 'NA'
## Warning: Expecting numeric in T834 / R834C20: got 'NA'
fishing.PNMCA <- filter(fishing.PNMCA, !is.na(fiche_n))
head(fishing.PNMCA)
## # A tibble: 6 × 52
## fiche_n id_sortie id_obs date saisie etat_mer temp force_vent
## <dbl> <chr> <chr> <dttm> <chr> <dbl> <dbl> <chr>
## 1 2 PECHLOIS2… PECHL… 2020-08-11 00:00:00 Laure… 0 NA NA
## 2 2 PECHLOIS2… PECHL… 2020-08-11 00:00:00 Laure… 0 NA NA
## 3 2 PECHLOIS2… PECHL… 2020-08-11 00:00:00 Laure… 0 NA NA
## 4 4 PECHLOIS2… PECHL… 2020-08-12 00:00:00 Laure… 0 NA NA
## 5 4 PECHLOIS2… PECHL… 2020-08-12 00:00:00 Laure… 0 NA NA
## 6 4 PECHLOIS2… PECHL… 2020-08-12 00:00:00 Laure… 0 NA NA
## # ℹ 44 more variables: direct_v <chr>, direct_h <chr>, nebulosite <chr>,
## # phase_lune <chr>, y_lat <dbl>, y_degre <dbl>, y_min_dec <dbl>,
## # y_lat_DD <dbl>, lat <chr>, x_lon <dbl>, x_degre <dbl>, x_min_dec <dbl>,
## # x_lon_DD <dbl>, long <chr>, mod_pech <chr>, prof_m <dbl>, nb_pecheur <dbl>,
## # heure_deb <dttm>, heure_enq <dttm>, heure_fin <dttm>,
## # temps_pech_effectif <dttm>, temps_peche_estime <dttm>, choix_site <chr>,
## # fond_rech <chr>, esp_cib <chr>, mort_app <chr>, mort_esp <chr>, …
names(fishing.PNMCA) # in contrast to the metadata file, the var id_enquete does not appear in the DB; in contrast to the DB, the var lat & long do not appear in the metadata
## [1] "fiche_n" "id_sortie" "id_obs"
## [4] "date" "saisie" "etat_mer"
## [7] "temp" "force_vent" "direct_v"
## [10] "direct_h" "nebulosite" "phase_lune"
## [13] "y_lat" "y_degre" "y_min_dec"
## [16] "y_lat_DD" "lat" "x_lon"
## [19] "x_degre" "x_min_dec" "x_lon_DD"
## [22] "long" "mod_pech" "prof_m"
## [25] "nb_pecheur" "heure_deb" "heure_enq"
## [28] "heure_fin" "temps_pech_effectif" "temps_peche_estime"
## [31] "choix_site" "fond_rech" "esp_cib"
## [34] "mort_app" "mort_esp" "viv_app"
## [37] "viv_esp" "app_autre" "procu_app"
## [40] "tech_util" "res_tour" "infraction"
## [43] "infraction_nb" "nom_scien" "nb_ind"
## [46] "tail_cm" "poids_g" "poids_sor"
## [49] "photos" "CPUE" "CPUE total"
## [52] "obs"
fishing.PNMCA$heure_deb <- as_hms(fishing.PNMCA$heure_deb)
fishing.PNMCA$heure_enq <- as_hms(fishing.PNMCA$heure_enq)
fishing.PNMCA$heure_fin <- as_hms(fishing.PNMCA$heure_fin)
fishing.PNMCA$temps_pech_effectif <- as_hms(fishing.PNMCA$temps_pech_effectif)
fishing.PNMCA$temps_peche_estime <- as_hms(fishing.PNMCA$temps_peche_estime)
# variables in common and diff
# common var
intersect(names(fishing.Stareso), names(fishing.PNMCA))
## [1] "fiche_n" "id_sortie" "id_obs" "date" "saisie"
## [6] "etat_mer" "temp" "force_vent" "direct_v" "direct_h"
## [11] "nebulosite" "phase_lune" "mod_pech" "prof_m" "nb_pecheur"
## [16] "heure_deb" "heure_enq" "heure_fin" "choix_site" "fond_rech"
## [21] "esp_cib" "mort_app" "mort_esp" "viv_app" "viv_esp"
## [26] "app_autre" "procu_app" "tech_util" "nom_scien" "nb_ind"
## [31] "tail_cm" "poids_g" "poids_sor" "photos" "CPUE"
## [36] "CPUE total" "obs"
# var in PNMCA but not in Stareso
setdiff(names(fishing.PNMCA), names(fishing.Stareso))
## [1] "y_lat" "y_degre" "y_min_dec"
## [4] "y_lat_DD" "lat" "x_lon"
## [7] "x_degre" "x_min_dec" "x_lon_DD"
## [10] "long" "temps_pech_effectif" "temps_peche_estime"
## [13] "res_tour" "infraction" "infraction_nb"
# var in Stareso but not in PNMCA
setdiff(names(fishing.Stareso), names(fishing.PNMCA))
## [1] "lat (°N)" "long (°E)" "zone_peche"
## [4] "temps_pech" "lieu_residence" "mode_de_pêche"
## [7] "zone_geographique"
# union
union(setdiff(names(fishing.PNMCA), names(fishing.Stareso)), setdiff(names(fishing.Stareso), names(fishing.PNMCA)))
## [1] "y_lat" "y_degre" "y_min_dec"
## [4] "y_lat_DD" "lat" "x_lon"
## [7] "x_degre" "x_min_dec" "x_lon_DD"
## [10] "long" "temps_pech_effectif" "temps_peche_estime"
## [13] "res_tour" "infraction" "infraction_nb"
## [16] "lat (°N)" "long (°E)" "zone_peche"
## [19] "temps_pech" "lieu_residence" "mode_de_pêche"
## [22] "zone_geographique"
#some var obviously are identical, although with diff names:
# "y_lat_DD" vs "lat (°N)"
# "x_lon_DD" vs "long ((°E)"
# "temps_pech_effectif" vs "temps_pech"
head(fishing.PNMCA$y_lat_DD)
## [1] 42.77700 42.77700 42.77700 42.86687 42.86687 42.86687
head(fishing.Stareso$`lat (°N)`)
## [1] 42.967 42.967 42.967 42.967 42.967 42.967
names(fishing.Stareso)[names(fishing.Stareso) == "lat (°N)"] <- "y_lat_DD"
head(fishing.PNMCA$x_lon_DD)
## [1] 9.477967 9.477967 9.477967 9.340717 9.340717 9.340717
head(fishing.Stareso$`long (°E)`)
## [1] 9.34874 9.34874 9.34874 9.34874 9.34874 9.34874
names(fishing.Stareso)[names(fishing.Stareso) == "long (°E)"] <- "x_lon_DD"
head(fishing.PNMCA$temps_peche_estime)
## 02:00:00
## 02:00:00
## 02:00:00
## 04:00:00
## 04:00:00
## 04:00:00
head(fishing.PNMCA$temps_pech_effectif)
## 01:30:00
## 01:30:00
## 01:30:00
## 04:30:00
## 04:30:00
## 04:30:00
head(fishing.Stareso$temps_pech) #should I consider Stareso temps_pech as PNMCA temps_pech_effectif or temps_peche_estime ? temps_pech_effectif seems to be more logical cfr field observation and only one temps_peche considered in Stareso DB.
## 03:15:00
## 03:15:00
## 03:15:00
## 03:15:00
## 03:15:00
## 03:15:00
names(fishing.Stareso)[names(fishing.Stareso) == "temps_pech"] <- "temps_pech_effectif"
# merge PNMCA & Stareso dfs and add BD variable to all dfs.
fishing.PNMCA <- add_column(fishing.PNMCA, BD = "PNMCA", .before = "fiche_n")
fishing.Stareso <- add_column(fishing.Stareso, BD = "Stareso", .before = "fiche_n")
fishing <- bind_rows(fishing.PNMCA, fishing.Stareso)
fishing <- fishing[, c(c(intersect(names(fishing.Stareso), names(fishing.PNMCA))), c(setdiff(names(fishing.PNMCA), names(fishing.Stareso))), c(setdiff(names(fishing.Stareso), names(fishing.PNMCA))))]
# compa DB
names(fishing)
## [1] "BD" "fiche_n" "id_sortie"
## [4] "id_obs" "date" "saisie"
## [7] "etat_mer" "temp" "force_vent"
## [10] "direct_v" "direct_h" "nebulosite"
## [13] "phase_lune" "y_lat_DD" "x_lon_DD"
## [16] "mod_pech" "prof_m" "nb_pecheur"
## [19] "heure_deb" "heure_enq" "heure_fin"
## [22] "temps_pech_effectif" "choix_site" "fond_rech"
## [25] "esp_cib" "mort_app" "mort_esp"
## [28] "viv_app" "viv_esp" "app_autre"
## [31] "procu_app" "tech_util" "nom_scien"
## [34] "nb_ind" "tail_cm" "poids_g"
## [37] "poids_sor" "photos" "CPUE"
## [40] "CPUE total" "obs" "y_lat"
## [43] "y_degre" "y_min_dec" "lat"
## [46] "x_lon" "x_degre" "x_min_dec"
## [49] "long" "temps_peche_estime" "res_tour"
## [52] "infraction" "infraction_nb" "zone_peche"
## [55] "lieu_residence" "mode_de_pêche" "zone_geographique"
names(survey)
## [1] "BD" "mode_eqt" "fiche_n"
## [4] "id_sortie" "id_obs" "date"
## [7] "Saisie" "etat_mer" "temp"
## [10] "force_v" "direct_v" "direct_h"
## [13] "neb" "phase_lune" "y_lat"
## [16] "y_degres" "y_min_dec" "y_lat_DD"
## [19] "lat" "x_lon" "x_degres"
## [22] "x_min_dec" "x_lon_DD" "mod_peche"
## [25] "prof_m_moyen" "nb_pecheur" "h_debut"
## [28] "heure_enq" "h_fin" "Temps_peche_effectif"
## [31] "Temps_peche_estime" "deb_sortie" "fin_sortie"
## [34] "obs" "act_peche" "debarq"
## [37] "commune" "code_insee" "res_tour"
## [40] "pdb" "csm" "pe"
## [43] "po" "espcib1" "espcib2"
## [46] "espcib3" "z_1" "z_2"
## [49] "z_3" "z_4" "z_6"
## [52] "z_7" "z_8" "z_9"
## [55] "z_54" "z_55" "z_56"
## [58] "z_57" "z_58" "z_59"
## [61] "z_60" "z_61" "esp_cib"
## [64] "mort_pss" "mort_cru" "mort_mll"
## [67] "mort_vers" "mort_esp" "viv_vers"
## [70] "viv_pss" "viv_cru" "viv_moll"
## [73] "autre" "viv_esp" "autre_app"
## [76] "procu_app" "agachon" "indienne"
## [79] "chas_trou" "tra_fond" "tra_surf"
## [82] "pierre" "palangro" "palangre"
## [85] "nasse" "ligne_m" "broume"
## [88] "flotteur" "peche_cal" "surfcas"
## [91] "pelote" "pierre_bd" "sout_bd"
## [94] "leurre_tt" "turlutte" "leur_surf"
## [97] "rockfish" "shad" "shore_jigg"
## [100] "jigging" "tenya" "madai"
## [103] "inchiku" "fireball" "autre_tech"
## [106] "prise_jour" "sexe" "age"
## [109] "age_moyen" "cat_pro" "act_pro"
## [112] "assoc" "nom_asso" "deb_age"
## [115] "temps_parc" "nb_sort_an" "j"
## [118] "f" "m" "a"
## [121] "m2" "j3" "j4"
## [124] "a5" "s" "o"
## [127] "n" "d" "niql"
## [130] "vac" "we" "sem"
## [133] "aube" "matin" "soir"
## [136] "crepuscule" "nuit" "apm"
## [139] "journee" "nimp_q" "p_no_kill"
## [142] "bag_thon" "doursin" "joursin"
## [145] "foursin" "moursin" "aoursin"
## [148] "pourc_sem" "pourc_we" "pour_jf"
## [151] "nb_sort_an6" "dur_sort" "secteur_po"
## [154] "secteur_po7" "douz_jour" "douz_jour8"
## [157] "nb_pech_o" "dur_moy_o" "nb_ours"
## [160] "nb_sous_tail" "poss_bat" "type_bat"
## [163] "motor" "longueur" "loca_bat"
## [166] "loca_dom" "port_atta" "gps"
## [169] "sondeur" "vivier" "table_traçante"
## [172] "vire_ligne" "autre9" "anc_posid"
## [175] "dep_pdb" "dep_pe" "dep_csm"
## [178] "dep_po" "co_pnmcca" "zone_pro"
## [181] "reg_pech_l" "reg_pech_o" "sais_pech_o"
## [184] "tail_min_o" "quot_max_o" "inf_pech_l"
## [187] "avis_mes_l" "avis_mes_o" "obs_stock_o"
## [190] "obs_stock_l" "q_esp" "raison_var"
## [193] "comm_rais_var" "solu_gest" "comm_gest"
## [196] "esp_n_ind" "nom_esp_ind" "res_alien"
## [199] "avis_pnm" "accessibilite" "proximite"
## [202] "connaissance" "recommandation" "autre10"
## [205] "abondance" "tranquilite" "fonds_rech"
setdiff(names(fishing), names(survey))
## [1] "saisie" "force_vent" "nebulosite"
## [4] "mod_pech" "prof_m" "heure_deb"
## [7] "heure_fin" "temps_pech_effectif" "choix_site"
## [10] "fond_rech" "mort_app" "viv_app"
## [13] "app_autre" "tech_util" "nom_scien"
## [16] "nb_ind" "tail_cm" "poids_g"
## [19] "poids_sor" "photos" "CPUE"
## [22] "CPUE total" "y_degre" "x_degre"
## [25] "long" "temps_peche_estime" "infraction"
## [28] "infraction_nb" "zone_peche" "lieu_residence"
## [31] "mode_de_pêche" "zone_geographique"
intersect(names(fishing), names(survey))
## [1] "BD" "fiche_n" "id_sortie" "id_obs" "date"
## [6] "etat_mer" "temp" "direct_v" "direct_h" "phase_lune"
## [11] "y_lat_DD" "x_lon_DD" "nb_pecheur" "heure_enq" "esp_cib"
## [16] "mort_esp" "viv_esp" "procu_app" "obs" "y_lat"
## [21] "y_min_dec" "lat" "x_lon" "x_min_dec" "res_tour"
#some variable do not coincide between fishing and survey dfs; we have to make names matching for comparison purpose between fishing vs survey!
class(fishing$mod_pech) ; class(survey$mod_peche)
## [1] "character"
## [1] "character"
names(fishing)[names(fishing) == "mod_pech"] <- "mod_peche"
class(fishing$lieu_residence) ; class(survey$commune)
## [1] "character"
## [1] "character"
names(fishing)[names(fishing) == "lieu_residence"] <- "commune"
class(fishing$x_lon) ; class(survey$x_degres)
## [1] "numeric"
## [1] "numeric"
names(fishing)[names(fishing) == "long (°E)"] <- "x_degres"
#NB: the var survey$x_degres makes no sense
class(fishing$y_lat) ; class(survey$y_degres)
## [1] "numeric"
## [1] "numeric"
names(fishing)[names(fishing) == "lat (°N)"] <- "y_degres"
#NB: the var survey$y_degres makes no sense
class(fishing$app_autre) ; class(survey$autre_app)
## [1] "character"
## [1] "character"
names(fishing)[names(fishing) == "app_autre"] <- "autre_app"
class(fishing$fond_rech) ; class(survey$fonds_rech)
## [1] "character"
## [1] "character"
names(fishing)[names(fishing) == "fond_rech"] <- "fonds_rech"
class(fishing$heure_enq) ; class(survey$heure_enq)
## [1] "hms" "difftime"
## [1] "hms" "difftime"
names(fishing)[names(fishing) == "heure_enq"] <- "heure_enq"
class(fishing$temps_pech_effectif) ; class(survey$Temps_peche_effectif)
## [1] "hms" "difftime"
## [1] "hms" "difftime"
names(fishing)[names(fishing) == "temps_pech_effectif"] <- "Temps_peche_effectif"
class(fishing$heure_fin) ; class(survey$h_fin)
## [1] "hms" "difftime"
## [1] "hms" "difftime"
names(fishing)[names(fishing) == "heure_fin"] <- "h_fin"
class(fishing$heure_deb) ; class(survey$h_debut)
## [1] "hms" "difftime"
## [1] "hms" "difftime"
names(fishing)[names(fishing) == "heure_deb"] <- "h_debut"
class(fishing$prof_m) ; class(survey$prof_m_moyen)
## [1] "numeric"
## [1] "character"
names(fishing)[names(fishing) == "prof_m"] <- "prof_m_moyen"
class(fishing$nebulosite) ; class(survey$neb)
## [1] "character"
## [1] "character"
#variable neb in survet DB can be changed to character cfr xx-xx% in fishing DB. Change we'll be made in case of DB fusion.
names(fishing)[names(fishing) == "nebulosite"] <- "neb"
class(fishing$force_vent) ; class(survey$force_v)
## [1] "character"
## [1] "character"
# format diff cfr not only num for fishing
names(fishing)[names(fishing) == "force_vent"] <- "force_v"
class(fishing$saisie) ; class(survey$Saisie)
## [1] "character"
## [1] "character"
names(fishing)[names(fishing) == "saisie"] <- "Saisie"
# some more step by step work on the data according to below code of analysis ####
head(survey$date)
## [1] "2020-08-11" "2020-08-11" "2020-08-12" "2020-08-12" "2020-08-12"
## [6] "2020-08-14"
survey %>% separate(date, into = c("a", "m", "j"), remove = F) -> survey
head(fishing$date)
## [1] "2020-08-11 UTC" "2020-08-11 UTC" "2020-08-11 UTC" "2020-08-12 UTC"
## [5] "2020-08-12 UTC" "2020-08-12 UTC"
fishing %>% separate(date, into = c("a", "m", "j"), remove = F) -> fishing
unique(survey$sexe)
## [1] "homme" "femme" "Homme" NA
survey$sexe <- ifelse(survey$sexe == "Homme", "homme", survey$sexe)
survey$age_moyen <- as.numeric(survey$age_moyen)
## Warning: NAs introduits lors de la conversion automatique
unique(fishing$mod_peche)
## [1] "csm" "pe" "pdb" "po" "PDB" "PE" "CSM"
fishing$mod_peche <- ifelse(fishing$mod_peche == "PDB", "pdb", fishing$mod_peche)
fishing$mod_peche <- ifelse(fishing$mod_peche == "PE", "pe", fishing$mod_peche)
fishing$mod_peche <- ifelse(fishing$mod_peche == "CSM", "csm", fishing$mod_peche)
saveRDS(survey, "Raw data_mined/enquetes.rds")
write.csv2(survey, "Raw data_mined/enquetes.csv")
saveRDS(fishing, "Raw data_mined/terrain.rds")
write.csv2(survey, "Raw data_mined/terrain.csv")
# update plot & analysis report 2022
# plot fishers vs sex ####
unique(survey$sexe)
## [1] "homme" "femme" NA
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
df. <- na.omit(survey[, c("a", "sexe")])
unique(df.$a)
## [1] "2020" "2021" "2022" "2023" "2024"
df. %>% filter(a %in% c("2020","2021","2022", "2023")) %>% group_by(sexe) %>% count() -> data
data <- data.frame(data)
data$fraction = (data$n/sum(data$n))*100
data
## sexe n fraction
## 1 femme 15 3.448276
## 2 homme 420 96.551724
ggplot(data, aes(x="", y=fraction, fill=sexe)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2020-2023 (n=", sum(data$n), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(fraction/100)), position = position_stack(vjust = 0.5)) # Ajouter les pourcentages
ggsave("Figs/Sex/sex_2020-2023.png", width = 5, height = 4)
df. %>% filter(a %in% c("2020","2021","2022")) %>% group_by(sexe) %>% count() -> data.1
data.1 <- data.frame(data.1)
data.1$fraction = (data.1$n/sum(data.1$n))*100
data.1
## sexe n fraction
## 1 femme 7 2.681992
## 2 homme 254 97.318008
ggplot(data.1, aes(x="", y=fraction, fill=sexe)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2020-2022 (n=", sum(data.1$n), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(fraction/100)), position = position_stack(vjust = 0.5)) # Ajouter les pourcentages
ggsave("Figs/Sex/sex_2020-2022.png", width = 5, height = 4)
df. %>% filter(a %in% c("2023")) %>% group_by(sexe) %>% count() -> data.2
data.2 <- data.frame(data.2)
data.2$fraction = (data.2$n/sum(data.2$n))*100
data.2
## sexe n fraction
## 1 femme 8 4.597701
## 2 homme 166 95.402299
ggplot(data.2, aes(x="", y=fraction, fill=sexe)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2023 (n=", sum(data.2$n), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(fraction/100)), position = position_stack(vjust = 0.5)) # Ajouter les pourcentages
ggsave("Figs/Sex/sex_2023.png", width = 5, height = 4)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%")))
# plot age pyramid by sex ####
unique(survey$sexe)
## [1] "homme" "femme" NA
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
unique(survey$age_moyen)
## [1] 50 45 25 35 15 20 30 56 46 53 60 80 31 51 36 55 71 43 72 14 63 62 68 41 38
## [26] 49 74 57 64 66 37 67 13 39 73 52 28 54 42 79 17 70 75 69 58 40 NA 61 77 23
## [51] 47 76 59 29 24 16 48 21
df. <- survey[, c("a", "sexe", "age_moyen")]
#df. <- na.omit(survey[, c("a", "sexe", "age_moyen")])
df.$sexe <- factor(df.$sexe, levels = c("femme", "homme"))
df. <- add_column(df., age_classe = NA, .after = "age_moyen")
df.$age_classe <- as.character(df.$age_classe)
df. <- data.frame(df.)
df.$age_classe <- ifelse(df.$age_moyen >= 70, "70 et plus", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 60 & df.$age_moyen < 70, "60-69", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 50 & df.$age_moyen < 60, "50-59", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 40 & df.$age_moyen < 50, "40-49", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 25 & df.$age_moyen < 40, "25-39", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen < 25, "13-24", df.$age_classe)
unique(df.$age_classe)
## [1] "50-59" "40-49" "25-39" "13-24" "60-69"
## [6] "70 et plus" NA
df.$age_classe <- as.factor(df.$age_classe)
df. %>% tabyl(age_classe, sexe)
## age_classe femme homme NA_
## 13-24 0 17 0
## 25-39 2 51 0
## 40-49 1 71 0
## 50-59 4 124 0
## 60-69 5 31 0
## 70 et plus 1 24 0
## <NA> 10 250 179
df. %>% tabyl(age_classe, sexe, a) #we have no info about age_moyen in 2023 so not possible to plot the age pyramid!
## $`2020`
## age_classe femme homme
## 13-24 0 2
## 25-39 0 13
## 40-49 1 27
## 50-59 1 58
## 60-69 0 0
## 70 et plus 0 0
##
## $`2021`
## age_classe femme homme
## 13-24 0 0
## 25-39 0 16
## 40-49 0 14
## 50-59 1 41
## 60-69 0 1
## 70 et plus 0 1
##
## $`2022`
## age_classe femme homme
## 13-24 0 3
## 25-39 1 10
## 40-49 0 19
## 50-59 1 14
## 60-69 2 19
## 70 et plus 0 15
## <NA> 0 1
##
## $`2023`
## age_classe femme homme
## 13-24 0 0
## 25-39 0 0
## 40-49 0 0
## 50-59 0 0
## 60-69 0 0
## 70 et plus 0 0
## <NA> 8 166
##
## $`2024`
## age_classe femme homme
## 13-24 0 0
## 25-39 0 0
## 40-49 0 0
## 50-59 0 0
## 60-69 0 0
## 70 et plus 0 0
## <NA> 2 80
##
## $NA_
## age_classe femme homme NA_
## 13-24 0 12 0
## 25-39 1 12 0
## 40-49 0 11 0
## 50-59 1 11 0
## 60-69 3 11 0
## 70 et plus 1 8 0
## <NA> 0 3 179
apyramid::age_pyramid(data = na.omit(df.),
age_group = "age_classe",
split_by = "sexe",
proportional = TRUE,
show_midpoint = FALSE)
na.omit(df.) %>% filter(a %in% c("2020","2021","2022")) -> data.1
# create dataset with proportion of total
pyramid_data <- data.1 %>%
count(age_classe,
sexe,
name = "counts") %>%
#ungroup() %>% # ungroup so percents are not by group
group_by(sexe) %>% # group by sex so percents are not by group
mutate(percent = round(100*(counts / sum(counts, na.rm=T)), digits = 1),
percent = case_when(
sexe == "homme" ~ percent,
sexe == "femme" ~ -percent, # convert male to negative
TRUE ~ NA_real_)) # NA val must by numeric as well
max_per <- max(pyramid_data$percent, na.rm=T)
min_per <- min(pyramid_data$percent, na.rm=T)
# begin ggplot
ggplot()+ # default x-axis is age in years;
# case data graph
geom_col(data = pyramid_data,
mapping = aes(
x = age_classe,
y = percent,
fill = sexe),
colour = "white")+ # white around each bar
# flip the X and Y axes to make pyramid vertical
coord_flip()+
# adjust the axes scales
# scale_x_continuous(breaks = seq(0,100,5), labels = seq(0,100,5)) +
scale_y_continuous(
limits = c(#min_per, max_per)
-50,50),
breaks = seq(from = -50 #floor(min_per)
, # sequence of values, by 2s
to = 50#ceiling(max_per)
,
by = 10),
labels = paste0(abs(seq(from = -50 #floor(min_per)
, # sequence of absolute values, by 2s, with "%"
to = 50 #ceiling(max_per)
,
by = 10)),
"%"))+
# designate colors and legend labels manually
scale_fill_manual(
values = c("femme" = "#F8766D",
"homme" = "#00BFC4"),
labels = c(paste0("femme (n=", sum((filter(pyramid_data, sexe=="femme"))[,"counts"], na.rm = T), ")"), paste0("homme (n=", sum((filter(pyramid_data, sexe=="homme"))[,"counts"], na.rm = T), ")")))+
# label values (remember X and Y flipped now)
labs(
title = "2020-2022",
x = "Classes d'âge",
y = "Pourcentage par sexe",
fill = NULL#,
#caption = stringr::str_glue("Data are from data.1 \nn = {nrow(data.1)} (age or sex missing for {sum(is.na(survey$sexe) | is.na(survey$age_moyen))} cases) \nData plot as of: {format(Sys.Date(), '%d %b %Y')}")
)+
# display themes
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
plot.title = element_text(hjust = 0.5),
plot.caption = element_text(hjust=0, size=11, face = "italic")
)
ggsave("Figs/pyramid.age_2020-2022.png", width = 7, height = 4)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%")))
# boxplot age vs fishing mode ####
unique(survey$mod_peche)
## [1] "pdb" "csm" "pe" "po" "pdb, csm" NA
table(survey$mod_peche)
##
## csm pdb pdb, csm pe po
## 38 326 2 151 2
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
df. <- survey[, c("age_moyen", "a", "mod_peche")]
unique(df.$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
table(df.[, c("a", "mod_peche")] %>% group_by(a, mod_peche))
## mod_peche
## a csm pdb pdb, csm pe po
## 2020 11 67 0 24 0
## 2021 2 21 0 50 1
## 2022 3 29 0 52 1
## 2023 21 131 2 20 0
## 2024 1 76 0 5 0
df. %>% filter(mod_peche != "pdb, csm") -> df.
table(df.$mod_peche)
##
## csm pdb pe po
## 38 326 151 2
df.$mod_peche <- ifelse(df.$mod_peche == "csm", "chasse sous-marine", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pdb", "peche du bord", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pe", "peche embarquée", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "po", "peche à l'oursin", df.$mod_peche)
table(df.$mod_peche)
##
## chasse sous-marine peche à l'oursin peche du bord peche embarquée
## 38 2 326 151
df.$mod_peche <- as.factor(df.$mod_peche)
df.$mod_peche <- factor(df.$mod_peche, levels = c("chasse sous-marine", "peche du bord", "peche embarquée", "peche à l'oursin"))
table(df.$mod_peche) #we have no info about age_moyen in 2023 so not possible to plot the age pyramid!
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 38 326 151 2
df. %>% filter(a %in% c("2020","2021","2022")) -> data.1
ggplot(filter(data.1, mod_peche != "peche à l'oursin"), aes(x=mod_peche, y=age_moyen)) +
geom_boxplot() +
xlab("mode de peche") +
ylab("âge") +
ggtitle("2020-2022") +
scale_x_discrete(drop=FALSE) +
scale_fill_manual(drop=FALSE) +
geom_point(data = filter(data.1, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = age_moyen)) +
stat_summary(fun.y=mean, geom="point", shape=20, size=5, color="red", fill="red") +
geom_point(data = filter(data.1, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = mean(unclass((filter(data.1, mod_peche == "peche à l'oursin")["age_moyen"]))$age_moyen)), shape=20, size=5, color="red", fill="red")
## Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
## ℹ Please use the `fun` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_boxplot()`).
## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_summary()`).
ggsave("Figs/mode.peche.vs.age_2020-2022.png", width = 5, height = 4)
## Warning: Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Removed 1 row containing non-finite outside the scale range (`stat_summary()`).
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%")))
# plot proportion mod_pech ####
unique(survey$mod_peche)
## [1] "pdb" "csm" "pe" "po" "pdb, csm" NA
table(survey$mod_peche)
##
## csm pdb pdb, csm pe po
## 38 326 2 151 2
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
df. <- survey[, c("age_moyen", "a", "mod_peche")]
unique(df.$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
table(df.[, c("a", "mod_peche")] %>% group_by(a, mod_peche))
## mod_peche
## a csm pdb pdb, csm pe po
## 2020 11 67 0 24 0
## 2021 2 21 0 50 1
## 2022 3 29 0 52 1
## 2023 21 131 2 20 0
## 2024 1 76 0 5 0
df. %>% filter(mod_peche != "pdb, csm") -> df.
table(df.$mod_peche)
##
## csm pdb pe po
## 38 326 151 2
df.$mod_peche <- ifelse(df.$mod_peche == "csm", "chasse sous-marine", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pdb", "peche du bord", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pe", "peche embarquée", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "po", "peche à l'oursin", df.$mod_peche)
table(df.$mod_peche)
##
## chasse sous-marine peche à l'oursin peche du bord peche embarquée
## 38 2 326 151
df.$mod_peche <- as.factor(df.$mod_peche)
df.$mod_peche <- factor(df.$mod_peche, levels = c("chasse sous-marine", "peche du bord", "peche embarquée", "peche à l'oursin"))
table(df.$mod_peche)
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 38 326 151 2
df. %>% filter(a %in% c("2020","2021","2022", "2023")) %>% group_by(mod_peche) %>% count() -> data
data <- data.frame(data)
data$fraction = (data$n/sum(data$n))*100
data
## mod_peche n fraction
## 1 chasse sous-marine 37 8.5450346
## 2 peche du bord 248 57.2748268
## 3 peche embarquée 146 33.7182448
## 4 peche à l'oursin 2 0.4618938
names(data) <- c("technique", "n", "fraction")
ggplot(data, aes(x="", y=n, fill=technique)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2020-2023 (n=", sum(data$n,na.rm = T), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
scale_fill_brewer(palette="Blues") +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = n), position = position_stack(vjust = 0.5))
ggsave("Figs/Technique.peche/tech_2020-2023.png", width = 7, height = 4)
df. %>% filter(a %in% c("2020","2021","2022")) %>% group_by(mod_peche) %>% count() -> data.1
data.1 <- data.frame(data.1)
data.1$fraction = (data.1$n/sum(data.1$n))*100
data.1
## mod_peche n fraction
## 1 chasse sous-marine 16 6.1302682
## 2 peche du bord 117 44.8275862
## 3 peche embarquée 126 48.2758621
## 4 peche à l'oursin 2 0.7662835
names(data.1) <- c("technique", "n", "fraction")
ggplot(data.1, aes(x="", y=n, fill=technique)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2020-2022 (n=", sum(data.1$n,na.rm = T), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
scale_fill_brewer(palette="Blues") +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = n), position = position_stack(vjust = 0.5))
ggsave("Figs/Technique.peche/tech_2020-2022.png", width = 7, height = 4)
df. %>% filter(a %in% c("2023")) %>% group_by(mod_peche) %>% count() -> data.2
data.2 <- data.frame(data.2)
data.2$fraction = (data.2$n/sum(data.2$n))*100
data.2
## mod_peche n fraction
## 1 chasse sous-marine 21 12.20930
## 2 peche du bord 131 76.16279
## 3 peche embarquée 20 11.62791
names(data.2) <- c("technique", "n", "fraction")
ggplot(data.2, aes(x="", y=n, fill=technique)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle(paste0("2023 (n=", sum(data.2$n,na.rm = T), ")")) +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
scale_fill_brewer(palette="Blues") +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = n), position = position_stack(vjust = 0.5))
ggsave("Figs/Technique.peche/tech_2023.png", width = 7, height = 4)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%")))
# prepare df. to perform multivariate analysis ####
# in below multivariate analysis, I have included all the variables of the survey df used in Michel 2022 report, among them those of the "AFM" (majority) but also those of the summary table and associated Kiviat diagram. For many varaibles, there are no data for year 2023 !
# => in 2O23: raw. var.: mod_peche, res_tour, sexe, Temps_peche_effectif, Temps_peche_estime, zone & zone.gp ("z_1","z_2","z_3","z_4","z_6","z_7","z_8","z_9","z_54","z_55","z_56","z_57","z_58","z_59","z_60","z_61")
# => not in 2023: raw var.: age_moyen (& age_classe), cat_pro (& cat_pro.gp), nb_sort_an (& nb_sort_an_cat), avis_pnm, poss_bat, dep (& dep.median, dep.mod.peche, etc) ; calculated var. : time.week ("we", "sem"), time.day & time.day.gp ("aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q")
unique(survey$mod_peche); length(na.omit(survey$mod_peche)) ; table(survey$mod_peche) ; table(survey$a, survey$mod_peche)
## [1] "pdb" "csm" "pe" "po" "pdb, csm" NA
## [1] 519
##
## csm pdb pdb, csm pe po
## 38 326 2 151 2
##
## csm pdb pdb, csm pe po
## 2020 11 67 0 24 0
## 2021 2 21 0 50 1
## 2022 3 29 0 52 1
## 2023 21 131 2 20 0
## 2024 1 76 0 5 0
unique(survey$age_moyen); length(na.omit(survey$age_moyen)) ; table(survey$age_moyen) ; table(survey$a, survey$age_moyen) #no data for 2023
## [1] 50 45 25 35 15 20 30 56 46 53 60 80 31 51 36 55 71 43 72 14 63 62 68 41 38
## [26] 49 74 57 64 66 37 67 13 39 73 52 28 54 42 79 17 70 75 69 58 40 NA 61 77 23
## [51] 47 76 59 29 24 16 48 21
## [1] 331
##
## 13 14 15 16 17 20 21 23 24 25 28 29 30 31 35 36 37 38 39 40
## 1 3 1 1 4 3 1 2 1 5 3 2 7 3 23 3 5 1 1 1
## 41 42 43 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
## 4 3 7 48 2 3 1 3 101 4 1 4 4 5 3 3 2 1 3 1
## 62 63 64 66 67 68 69 70 71 72 73 74 75 76 77 79 80
## 5 6 5 5 3 4 4 4 4 2 2 6 1 1 2 1 2
##
## 13 14 15 16 17 20 21 23 24 25 28 29 30 31 35 36 37 38 39 40 41 42 43 45
## 2020 0 0 1 0 0 1 0 0 0 3 0 0 0 0 10 0 0 0 0 0 0 0 0 28
## 2021 0 0 0 0 0 0 0 0 0 1 0 0 1 1 12 1 0 0 0 0 0 0 0 13
## 2022 1 1 0 0 1 0 0 0 0 0 1 0 2 1 0 1 4 1 1 1 3 2 5 6
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 66 67 68 69 70
## 2020 0 0 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2021 1 0 0 0 39 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0
## 2022 1 0 0 1 1 3 1 2 2 3 0 2 1 0 1 1 3 4 2 2 1 4 3 3
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## 71 72 73 74 75 76 77 79 80
## 2020 0 0 0 0 0 0 0 0 0
## 2021 0 0 0 0 0 0 0 0 1
## 2022 2 2 2 2 1 0 1 1 1
## 2023 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0
#profil ?? #not possible to find out what is the "profil" group of/unique variables used by Michel in the MFA!
unique(survey$act_pro); length(na.omit(survey$act_pro)) ; table(survey$act_pro) ; table(survey$a, survey$act_pro) #no sense to many categories, or merge act_pro ; no data for 2023; not considered in the analysis.
## [1] "Artisan(e)s,_commerçant(e)s_et_chef(fe)_d'entreprises"
## [2] "Cadres_et_profession_intellectuelles_superieures"
## [3] "Employe(e)s"
## [4] "Retraite(e)s"
## [5] "Sans_emploi"
## [6] "Agriculteur"
## [7] "Chomeur"
## [8] "Retraite"
## [9] "Vendeur"
## [10] "Livreur"
## [11] "Chef_d'entreprise"
## [12] "Peintre"
## [13] "Enseignante"
## [14] "Responsable_securite"
## [15] "Enseignant"
## [16] "Maçon"
## [17] "Agent_securite"
## [18] "Comptable"
## [19] "Restaurateur"
## [20] "Magasinier"
## [21] "Ingenieur"
## [22] "Etudiant"
## [23] "Agent_entretien"
## [24] "Electricien"
## [25] "Infirmier"
## [26] "Informaticien"
## [27] "Reparateur_electromenager"
## [28] "Vendeuse"
## [29] "Boucher"
## [30] "Kinesitherapeute"
## [31] "Aide_soignant"
## [32] "Vigneron"
## [33] "Policier_aux_frontieres"
## [34] "Tatoueur"
## [35] "Ingenieur_"
## [36] "Marayeur"
## [37] "Vendeur_de_materiel_de_peche"
## [38] "Terrassier"
## [39] "Artisan_"
## [40] "Taxi"
## [41] "Ingenieur_en_aquaculture"
## [42] "Pompier"
## [43] "Retraite_"
## [44] "Assurance_"
## [45] "Gerant_de_societe"
## [46] "fonctionnaire"
## [47] "Technicien"
## [48] "Agent_territorial_"
## [49] "Cadre_dans_l'environnement"
## [50] "Architecte"
## [51] "Banquier"
## [52] "Commerçant_"
## [53] "Commerçant"
## [54] "Conducteur"
## [55] "Location_de_gîtes"
## [56] "gardien"
## [57] "commercial"
## [58] "retraite"
## [59] "chef d'entreprise"
## [60] "retraire"
## [61] "employe au port"
## [62] "restaurateur"
## [63] "plombier"
## [64] "commerçant"
## [65] "chomeur"
## [66] "artisan"
## [67] "employe"
## [68] "moniteur de peche"
## [69] "medecin"
## [70] "sans emploi"
## [71] "marin commerce"
## [72] "maçon"
## [73] "NA"
## [74] "ingenieur"
## [75] "ebeniste"
## [76] "serrurier"
## [77] "nA"
## [78] "employe office HLM"
## [79] "artisan peintre"
## [80] "agent entretien mairie Oletta"
## [81] "paysagiste"
## [82] "professeur"
## [83] "agent commercial"
## [84] "restauration"
## [85] "livreur"
## [86] "boulanger"
## [87] "agent OFB"
## [88] "marin"
## [89] "location bateaux"
## [90] "CC de Saint-Florent"
## [91] "ouvrier"
## [92] "chauffeur"
## [93] "menuisier"
## [94] "gent de terrain PNMCCA"
## [95] "transition"
## [96] "technicien"
## [97] "transporteur de fond"
## [98] "banquier"
## [99] "garde_forestier"
## [100] "lyceen"
## [101] "infirmier"
## [102] "sans_emploi"
## [103] "geometre"
## [104] "entrepreneur"
## [105] "agent immobilier"
## [106] "couvreur"
## [107] "manager"
## [108] "professeur de tennis"
## [109] NA
## [110] "activite"
## [111] "etudiant"
## [1] 509
##
## activite
## 41
## agent commercial
## 1
## agent entretien mairie Oletta
## 1
## agent immobilier
## 1
## agent OFB
## 1
## Agent_entretien
## 1
## Agent_securite
## 1
## Agent_territorial_
## 1
## Agriculteur
## 1
## Aide_soignant
## 2
## Architecte
## 1
## artisan
## 7
## artisan peintre
## 1
## Artisan(e)s,_commerçant(e)s_et_chef(fe)_d'entreprises
## 4
## Artisan_
## 2
## Assurance_
## 1
## banquier
## 1
## Banquier
## 1
## Boucher
## 1
## boulanger
## 1
## Cadre_dans_l'environnement
## 1
## Cadres_et_profession_intellectuelles_superieures
## 2
## CC de Saint-Florent
## 1
## chauffeur
## 1
## chef d'entreprise
## 2
## Chef_d'entreprise
## 2
## chomeur
## 1
## Chomeur
## 1
## commerçant
## 2
## Commerçant
## 1
## Commerçant_
## 1
## commercial
## 3
## Comptable
## 2
## Conducteur
## 1
## couvreur
## 1
## ebeniste
## 1
## Electricien
## 2
## employe
## 1
## employe au port
## 1
## employe office HLM
## 1
## Employe(e)s
## 1
## Enseignant
## 1
## Enseignante
## 1
## entrepreneur
## 1
## etudiant
## 7
## Etudiant
## 1
## fonctionnaire
## 5
## garde_forestier
## 1
## gardien
## 1
## gent de terrain PNMCCA
## 1
## geometre
## 1
## Gerant_de_societe
## 1
## infirmier
## 1
## Infirmier
## 2
## Informaticien
## 1
## ingenieur
## 1
## Ingenieur
## 1
## Ingenieur_
## 1
## Ingenieur_en_aquaculture
## 1
## Kinesitherapeute
## 1
## livreur
## 1
## Livreur
## 2
## location bateaux
## 1
## Location_de_gîtes
## 1
## lyceen
## 1
## maçon
## 1
## Maçon
## 2
## Magasinier
## 1
## manager
## 1
## Marayeur
## 1
## marin
## 3
## marin commerce
## 1
## medecin
## 1
## menuisier
## 1
## moniteur de peche
## 1
## nA
## 1
## NA
## 197
## ouvrier
## 1
## paysagiste
## 3
## Peintre
## 3
## plombier
## 2
## Policier_aux_frontieres
## 1
## Pompier
## 1
## professeur
## 1
## professeur de tennis
## 1
## Reparateur_electromenager
## 1
## Responsable_securite
## 1
## restaurateur
## 3
## Restaurateur
## 3
## restauration
## 1
## retraire
## 1
## retraite
## 50
## Retraite
## 51
## Retraite(e)s
## 1
## Retraite_
## 2
## sans emploi
## 1
## sans_emploi
## 5
## Sans_emploi
## 17
## serrurier
## 1
## Tatoueur
## 1
## Taxi
## 1
## technicien
## 1
## Technicien
## 1
## Terrassier
## 1
## transition
## 1
## transporteur de fond
## 1
## Vendeur
## 1
## Vendeur_de_materiel_de_peche
## 1
## Vendeuse
## 1
## Vigneron
## 1
##
## activite agent commercial agent entretien mairie Oletta agent immobilier
## 2020 0 0 0 0
## 2021 0 0 0 0
## 2022 0 1 1 1
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## agent OFB Agent_entretien Agent_securite Agent_territorial_ Agriculteur
## 2020 0 1 1 0 1
## 2021 0 0 0 1 0
## 2022 1 0 0 0 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## Aide_soignant Architecte artisan artisan peintre
## 2020 1 0 0 0
## 2021 1 1 4 0
## 2022 0 0 3 1
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## Artisan(e)s,_commerçant(e)s_et_chef(fe)_d'entreprises Artisan_
## 2020 4 0
## 2021 0 2
## 2022 0 0
## 2023 0 0
## 2024 0 0
##
## Assurance_ banquier Banquier Boucher boulanger
## 2020 0 0 0 1 0
## 2021 1 0 1 0 0
## 2022 0 1 0 0 1
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## Cadre_dans_l'environnement
## 2020 0
## 2021 1
## 2022 0
## 2023 0
## 2024 0
##
## Cadres_et_profession_intellectuelles_superieures CC de Saint-Florent
## 2020 2 0
## 2021 0 0
## 2022 0 1
## 2023 0 0
## 2024 0 0
##
## chauffeur chef d'entreprise Chef_d'entreprise chomeur Chomeur commerçant
## 2020 0 0 2 0 1 0
## 2021 0 1 0 1 0 2
## 2022 1 1 0 0 0 0
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## Commerçant Commerçant_ commercial Comptable Conducteur couvreur ebeniste
## 2020 0 0 0 1 0 0 0
## 2021 1 1 1 1 1 0 1
## 2022 0 0 2 0 0 1 0
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
##
## Electricien employe employe au port employe office HLM Employe(e)s
## 2020 1 0 0 0 1
## 2021 1 1 1 0 0
## 2022 0 0 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## Enseignant Enseignante entrepreneur etudiant Etudiant fonctionnaire
## 2020 1 1 0 0 1 0
## 2021 0 0 0 0 0 2
## 2022 0 0 1 0 0 3
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## garde_forestier gardien gent de terrain PNMCCA geometre
## 2020 0 0 0 0
## 2021 0 1 0 0
## 2022 1 0 1 1
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## Gerant_de_societe infirmier Infirmier Informaticien ingenieur Ingenieur
## 2020 0 0 2 1 0 1
## 2021 1 0 0 0 1 0
## 2022 0 1 0 0 0 0
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## Ingenieur_ Ingenieur_en_aquaculture Kinesitherapeute livreur Livreur
## 2020 0 0 1 0 2
## 2021 1 1 0 0 0
## 2022 0 0 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## location bateaux Location_de_gîtes lyceen maçon Maçon Magasinier manager
## 2020 0 0 0 0 2 1 0
## 2021 0 1 0 1 0 0 0
## 2022 1 0 1 0 0 0 1
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
##
## Marayeur marin marin commerce medecin menuisier moniteur de peche nA
## 2020 0 0 0 0 0 0 0
## 2021 1 0 1 1 0 1 0
## 2022 0 3 0 0 1 0 1
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
##
## NA ouvrier paysagiste Peintre plombier Policier_aux_frontieres Pompier
## 2020 0 0 0 3 0 1 0
## 2021 2 0 0 0 1 0 1
## 2022 19 1 3 0 1 0 0
## 2023 174 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
##
## professeur professeur de tennis Reparateur_electromenager
## 2020 0 0 1
## 2021 0 0 0
## 2022 1 1 0
## 2023 0 0 0
## 2024 0 0 0
##
## Responsable_securite restaurateur Restaurateur restauration retraire
## 2020 1 0 1 0 0
## 2021 0 2 2 0 1
## 2022 0 1 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## retraite Retraite Retraite(e)s Retraite_ sans emploi sans_emploi
## 2020 0 44 1 0 0 0
## 2021 12 7 0 2 1 0
## 2022 18 0 0 0 0 1
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## Sans_emploi serrurier Tatoueur Taxi technicien Technicien Terrassier
## 2020 16 0 1 0 0 0 0
## 2021 1 0 0 1 0 1 1
## 2022 0 1 0 0 1 0 0
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
##
## transition transporteur de fond Vendeur Vendeur_de_materiel_de_peche
## 2020 0 0 1 0
## 2021 0 0 0 1
## 2022 1 1 0 0
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## Vendeuse Vigneron
## 2020 1 1
## 2021 0 0
## 2022 0 0
## 2023 0 0
## 2024 0 0
unique(survey$cat_pro); length(na.omit(survey$cat_pro)) ; table(survey$cat_pro) ; table(survey$a, survey$cat_pro) #no data for 2023
## [1] "activite" "retraite" "sans_emploi" "etudiant" "NA"
## [6] "en_arret" NA
## [1] 509
##
## activite en_arret etudiant NA retraite sans_emploi
## 175 3 11 177 118 25
##
## activite en_arret etudiant NA retraite sans_emploi
## 2020 40 0 1 0 45 16
## 2021 47 1 0 1 23 2
## 2022 47 2 3 0 30 3
## 2023 0 0 0 174 0 0
## 2024 0 0 0 0 0 0
unique(survey$nb_sort_an); length(na.omit(survey$nb_sort_an)) ; table(survey$nb_sort_an) ; table(survey$a, survey$nb_sort_an) #no data for 2023
## [1] "5" "30" "15" "40" "0" "10"
## [7] "1" "50" "64" "48" "80" "20"
## [13] "illimite" "150" "24" "130" "52" "100"
## [19] "25" "4" "60" "12" "2" "22"
## [25] "NA" NA "35" "200" "6" "7"
## [31] "250" "8"
## [1] 509
##
## 0 1 10 100 12 130 15 150
## 3 8 19 8 4 1 82 3
## 2 20 200 22 24 25 250 30
## 5 18 1 1 2 4 1 52
## 35 4 40 48 5 50 52 6
## 1 3 31 1 46 14 1 2
## 60 64 7 8 80 illimite NA
## 5 1 1 1 2 12 176
##
## 0 1 10 100 12 130 15 150 2 20 200 22 24 25 250 30 35 4
## 2020 1 0 0 0 0 0 59 0 0 0 0 0 0 0 0 8 0 0
## 2021 0 1 1 0 0 0 13 0 0 0 0 0 0 0 0 21 0 0
## 2022 1 6 11 4 3 1 4 1 2 9 0 1 2 1 0 11 0 3
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## 40 48 5 50 52 6 60 64 7 8 80 illimite NA
## 2020 1 0 33 0 0 0 0 0 0 0 0 0 0
## 2021 24 1 10 1 0 0 0 1 0 0 1 0 0
## 2022 2 0 1 7 1 0 2 0 0 0 0 12 0
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 174
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0
unique(survey$avis_pnm); length(na.omit(survey$avis_pnm)) ; table(survey$avis_pnm) ; table(survey$a, survey$avis_pnm) #no data for 2023
## [1] "p_avis" "t_positif" "positif" "nsp" "_" "negatif"
## [7] "t_negatif" "NA" NA
## [1] 509
##
## _ NA negatif nsp p_avis positif t_negatif t_positif
## 1 176 5 31 26 120 1 149
##
## _ NA negatif nsp p_avis positif t_negatif t_positif
## 2020 0 0 0 8 8 15 0 71
## 2021 1 0 0 3 3 37 0 30
## 2022 0 0 1 12 6 40 1 25
## 2023 0 174 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0
unique(survey$res_tour); length(na.omit(survey$res_tour)) ; table(survey$res_tour) ; table(survey$a, survey$res_tour)
## [1] "resident" "secondaire" "occasionnel" "touriste" NA
## [1] 591
##
## occasionnel resident secondaire touriste
## 26 454 40 71
##
## occasionnel resident secondaire touriste
## 2020 21 71 10 0
## 2021 3 70 1 0
## 2022 1 63 6 15
## 2023 1 116 9 48
## 2024 0 78 0 4
unique(survey$sexe); length(na.omit(survey$sexe)) ; table(survey$sexe) ; table(survey$a, survey$sexe) #no data for 2023
## [1] "homme" "femme" NA
## [1] 591
##
## femme homme
## 23 568
##
## femme homme
## 2020 2 100
## 2021 1 73
## 2022 4 81
## 2023 8 166
## 2024 2 80
unique(survey$poss_bat); length(na.omit(survey$poss_bat)) ; table(survey$poss_bat) ; table(survey$a, survey$poss_bat)
## [1] "non" "oui" "NA" NA
## [1] 509
##
## NA non oui
## 248 138 123
##
## NA non oui
## 2020 0 82 20
## 2021 0 25 49
## 2022 0 31 54
## 2023 174 0 0
## 2024 0 0 0
unique(survey$Temps_peche_effectif); length(na.omit(survey$Temps_peche_effectif)) ; table(survey$Temps_peche_effectif) ; table(survey$a, survey$Temps_peche_effectif)
## 00:30:00
## 01:30:00
## 04:30:00
## 05:00:00
## 00:45:00
## 01:05:00
## 04:25:00
## 01:45:00
## 00:00:00
## 00:15:00
## 02:15:00
## 00:50:00
## 01:00:00
## 01:40:00
## 02:40:00
## 02:05:00
## 01:20:00
## 02:00:00
## 03:00:00
## 01:50:00
## 01:35:00
## 01:55:00
## 04:20:00
## 00:05:00
## 01:10:00
## 03:25:00
## 04:00:00
## 02:45:00
## 02:10:00
## 01:15:00
## 03:15:00
## 00:40:00
## 04:05:00
## 03:20:00
## 03:35:00
## 03:30:00
## 04:40:00
## 00:10:00
## 00:20:00
## 01:17:00
## 05:35:00
## 05:17:00
## 04:38:00
## 05:26:00
## 03:57:00
## 03:21:00
## 04:57:00
## 00:02:00
## 02:01:00
## 01:02:00
## 04:10:00
## 05:08:00
## 08:00:00
## 03:51:00
## 01:38:00
## 03:18:00
## 04:49:00
## 02:46:00
## 05:02:00
## 00:11:00
## 04:23:00
## 01:51:00
## 03:38:00
## 01:12:00
## 03:45:00
## 01:47:00
## 02:23:00
## 00:33:00
## 04:18:00
## 03:26:00
## 02:02:00
## 00:55:00
## 00:23:00
## 02:38:00
## 01:13:00
## 01:53:00
## 04:22:00
## 02:06:00
## 01:19:00
## 01:04:00
## 01:49:00
## 02:20:00
## 06:41:00
## 03:50:00
## 01:42:00
## 02:30:00
## 04:53:00
## 03:39:00
## 02:03:00
## 01:46:00
## 04:19:00
## 00:21:00
## 00:59:00
## 03:27:00
## 01:08:00
## 02:24:00
## 01:52:00
## 01:37:00
## 02:53:00
## 05:10:00
## 00:01:00
## 01:39:00
## 02:50:00
## 02:35:00
## 03:43:00
## 03:54:00
## 01:43:00
## 04:58:00
## 05:15:00
## 06:30:00
## 07:36:00
## 06:59:00
## 00:54:00
## 09:00:00
## 02:51:00
## 01:54:00
## 04:39:00
## 02:37:00
## 04:35:00
## 00:07:00
## 03:13:00
## 04:04:00
## 05:12:00
## 06:20:00
## 05:40:00
## 00:58:00
## 01:09:00
## 01:28:00
## 02:16:00
## 06:10:00
## 06:45:00
## 10:00:00
## 05:30:00
## 07:30:00
## 06:00:00
## 08:10:00
## 00:35:00
## NA
## [1] 698
##
## 00:00:00 00:01:00 00:02:00 00:05:00 00:07:00 00:10:00 00:11:00 00:15:00
## 191 2 3 3 1 8 1 7
## 00:20:00 00:21:00 00:23:00 00:30:00 00:33:00 00:35:00 00:40:00 00:45:00
## 6 1 1 28 1 1 10 20
## 00:50:00 00:54:00 00:55:00 00:58:00 00:59:00 01:00:00 01:02:00 01:04:00
## 9 1 4 1 1 38 1 1
## 01:05:00 01:08:00 01:09:00 01:10:00 01:12:00 01:13:00 01:15:00 01:17:00
## 5 1 1 6 1 2 14 1
## 01:19:00 01:20:00 01:28:00 01:30:00 01:35:00 01:37:00 01:38:00 01:39:00
## 1 9 1 24 3 3 1 1
## 01:40:00 01:42:00 01:43:00 01:45:00 01:46:00 01:47:00 01:49:00 01:50:00
## 10 1 1 13 2 1 1 7
## 01:51:00 01:52:00 01:53:00 01:54:00 01:55:00 02:00:00 02:01:00 02:02:00
## 1 1 1 1 3 22 1 1
## 02:03:00 02:05:00 02:06:00 02:10:00 02:15:00 02:16:00 02:20:00 02:23:00
## 1 3 2 8 12 1 2 1
## 02:24:00 02:30:00 02:35:00 02:37:00 02:38:00 02:40:00 02:45:00 02:46:00
## 1 21 2 2 1 6 6 2
## 02:50:00 02:51:00 02:53:00 03:00:00 03:13:00 03:15:00 03:18:00 03:20:00
## 9 1 1 15 2 6 2 6
## 03:21:00 03:25:00 03:26:00 03:27:00 03:30:00 03:35:00 03:38:00 03:39:00
## 2 4 1 1 12 1 1 1
## 03:43:00 03:45:00 03:50:00 03:51:00 03:54:00 03:57:00 04:00:00 04:04:00
## 1 2 5 1 1 1 8 1
## 04:05:00 04:10:00 04:18:00 04:19:00 04:20:00 04:22:00 04:23:00 04:25:00
## 1 3 1 1 4 1 1 1
## 04:30:00 04:35:00 04:38:00 04:39:00 04:40:00 04:49:00 04:53:00 04:57:00
## 4 2 1 1 2 2 1 1
## 04:58:00 05:00:00 05:02:00 05:08:00 05:10:00 05:12:00 05:15:00 05:17:00
## 1 5 1 1 1 1 3 1
## 05:26:00 05:30:00 05:35:00 05:40:00 06:00:00 06:10:00 06:20:00 06:30:00
## 1 2 1 1 1 1 2 1
## 06:41:00 06:45:00 06:59:00 07:30:00 07:36:00 08:00:00 08:10:00 09:00:00
## 1 1 1 2 1 1 1 1
## 10:00:00
## 1
##
## 00:00:00 00:01:00 00:02:00 00:05:00 00:07:00 00:10:00 00:11:00 00:15:00
## 2020 2 0 0 2 0 4 0 6
## 2021 1 0 2 1 0 2 1 0
## 2022 1 2 1 0 1 1 0 0
## 2023 7 0 0 0 0 1 0 0
## 2024 1 0 0 0 0 0 0 1
##
## 00:20:00 00:21:00 00:23:00 00:30:00 00:33:00 00:35:00 00:40:00 00:45:00
## 2020 2 0 0 8 0 0 3 5
## 2021 0 0 1 1 1 0 0 1
## 2022 0 1 0 2 0 0 1 2
## 2023 2 0 0 9 0 0 5 10
## 2024 2 0 0 7 0 1 1 2
##
## 00:50:00 00:54:00 00:55:00 00:58:00 00:59:00 01:00:00 01:02:00 01:04:00
## 2020 4 0 0 0 0 6 0 0
## 2021 1 0 2 0 0 2 1 1
## 2022 0 1 1 0 1 3 0 0
## 2023 1 0 0 1 0 12 0 0
## 2024 3 0 1 0 0 15 0 0
##
## 01:05:00 01:08:00 01:09:00 01:10:00 01:12:00 01:13:00 01:15:00 01:17:00
## 2020 3 0 0 1 0 0 5 0
## 2021 0 0 0 1 1 1 1 1
## 2022 1 1 0 0 0 1 1 0
## 2023 0 0 1 3 0 0 5 0
## 2024 1 0 0 1 0 0 2 0
##
## 01:19:00 01:20:00 01:28:00 01:30:00 01:35:00 01:37:00 01:38:00 01:39:00
## 2020 0 2 0 3 2 0 0 0
## 2021 1 1 0 2 0 0 1 0
## 2022 0 1 0 0 0 2 0 1
## 2023 0 5 1 15 1 1 0 0
## 2024 0 0 0 4 0 0 0 0
##
## 01:40:00 01:42:00 01:43:00 01:45:00 01:46:00 01:47:00 01:49:00 01:50:00
## 2020 2 0 0 6 0 0 0 4
## 2021 0 0 0 1 0 1 1 0
## 2022 2 1 1 0 1 0 0 1
## 2023 6 0 0 3 1 0 0 1
## 2024 0 0 0 3 0 0 0 0
##
## 01:51:00 01:52:00 01:53:00 01:54:00 01:55:00 02:00:00 02:01:00 02:02:00
## 2020 0 0 0 0 3 3 0 0
## 2021 1 0 1 0 0 1 1 1
## 2022 0 1 0 1 0 1 0 0
## 2023 0 0 0 0 0 9 0 0
## 2024 0 0 0 0 0 8 0 0
##
## 02:03:00 02:05:00 02:06:00 02:10:00 02:15:00 02:16:00 02:20:00 02:23:00
## 2020 0 2 0 1 4 0 0 0
## 2021 0 0 1 1 0 0 1 1
## 2022 1 1 1 0 3 0 0 0
## 2023 0 0 0 5 4 1 1 0
## 2024 0 0 0 1 1 0 0 0
##
## 02:24:00 02:30:00 02:35:00 02:37:00 02:38:00 02:40:00 02:45:00 02:46:00
## 2020 0 0 0 0 0 1 1 0
## 2021 0 0 0 0 1 1 2 1
## 2022 1 1 2 1 0 2 1 1
## 2023 0 12 0 0 0 2 1 0
## 2024 0 8 0 1 0 0 1 0
##
## 02:50:00 02:51:00 02:53:00 03:00:00 03:13:00 03:15:00 03:18:00 03:20:00
## 2020 0 0 0 1 0 2 0 3
## 2021 0 0 0 2 0 0 2 0
## 2022 1 1 1 2 2 1 0 0
## 2023 7 0 0 5 0 2 0 1
## 2024 1 0 0 5 0 1 0 2
##
## 03:21:00 03:25:00 03:26:00 03:27:00 03:30:00 03:35:00 03:38:00 03:39:00
## 2020 0 2 0 0 1 1 0 0
## 2021 2 0 1 0 1 0 1 0
## 2022 0 2 0 1 2 0 0 1
## 2023 0 0 0 0 8 0 0 0
## 2024 0 0 0 0 0 0 0 0
##
## 03:43:00 03:45:00 03:50:00 03:51:00 03:54:00 03:57:00 04:00:00 04:04:00
## 2020 0 0 0 0 0 0 1 0
## 2021 0 1 1 1 0 1 0 0
## 2022 1 0 0 0 1 0 1 1
## 2023 0 1 3 0 0 0 3 0
## 2024 0 0 1 0 0 0 3 0
##
## 04:05:00 04:10:00 04:18:00 04:19:00 04:20:00 04:22:00 04:23:00 04:25:00
## 2020 1 0 0 0 1 0 0 1
## 2021 0 2 1 0 0 1 1 0
## 2022 0 1 0 1 0 0 0 0
## 2023 0 0 0 0 1 0 0 0
## 2024 0 0 0 0 2 0 0 0
##
## 04:30:00 04:35:00 04:38:00 04:39:00 04:40:00 04:49:00 04:53:00 04:57:00
## 2020 1 0 0 0 1 0 0 0
## 2021 1 0 1 0 0 1 0 1
## 2022 0 2 0 1 0 1 1 0
## 2023 2 0 0 0 1 0 0 0
## 2024 0 0 0 0 0 0 0 0
##
## 04:58:00 05:00:00 05:02:00 05:08:00 05:10:00 05:12:00 05:15:00 05:17:00
## 2020 0 1 0 0 0 0 0 0
## 2021 0 0 1 1 0 0 0 1
## 2022 1 1 0 0 1 1 2 0
## 2023 0 3 0 0 0 0 1 0
## 2024 0 0 0 0 0 0 0 0
##
## 05:26:00 05:30:00 05:35:00 05:40:00 06:00:00 06:10:00 06:20:00 06:30:00
## 2020 0 0 0 0 0 0 0 0
## 2021 1 0 1 0 0 0 0 0
## 2022 0 0 0 0 0 0 0 1
## 2023 0 1 0 1 1 1 2 0
## 2024 0 1 0 0 0 0 0 0
##
## 06:41:00 06:45:00 06:59:00 07:30:00 07:36:00 08:00:00 08:10:00 09:00:00
## 2020 0 0 0 0 0 0 0 0
## 2021 1 0 0 0 0 1 0 0
## 2022 0 0 1 0 1 0 0 1
## 2023 0 1 0 2 0 0 0 0
## 2024 0 0 0 0 0 0 1 0
##
## 10:00:00
## 2020 0
## 2021 0
## 2022 0
## 2023 1
## 2024 0
unique(survey$Temps_peche_estime); length(na.omit(survey$Temps_peche_estime)) ; table(survey$Temps_peche_estime) ; table(survey$a, survey$Temps_peche_estime)
## 02:00:00
## 01:30:00
## 04:00:00
## 04:30:00
## 05:00:00
## 03:30:00
## 01:00:00
## 03:00:00
## 02:30:00
## 06:30:00
## 05:30:00
## 02:35:00
## 01:40:00
## 07:00:00
## 08:00:00
## 09:30:00
## 06:00:00
## 03:02:00
## 05:50:00
## 09:00:00
## 11:00:00
## 10:00:00
## 08:30:00
## 13:00:00
## 02:20:00
## 07:15:00
## 00:45:00
## 01:35:00
## 01:10:00
## 03:45:00
## 03:36:00
## 02:15:00
## 01:05:00
## 02:01:00
## 04:15:00
## 07:55:00
## 00:30:00
## 02:45:00
## 04:10:00
## 03:20:00
## 12:00:00
## 07:30:00
## 15:00:00
## 03:15:00
## 08:15:00
## 04:45:00
## 18:30:00
## 01:45:00
## 02:50:00
## 03:50:00
## 02:40:00
## 00:40:00
## 17:00:00
## 02:10:00
## 08:10:00
## 00:50:00
## 04:50:00
## 00:00:00
## NA
## [1] 698
##
## 00:00:00 00:30:00 00:40:00 00:45:00 00:50:00 01:00:00 01:05:00 01:10:00
## 179 1 2 2 2 14 2 1
## 01:30:00 01:35:00 01:40:00 01:45:00 02:00:00 02:01:00 02:10:00 02:15:00
## 29 2 3 2 75 1 1 5
## 02:20:00 02:30:00 02:35:00 02:40:00 02:45:00 02:50:00 03:00:00 03:02:00
## 1 21 1 1 4 2 66 1
## 03:15:00 03:20:00 03:30:00 03:36:00 03:45:00 03:50:00 04:00:00 04:10:00
## 4 2 39 1 2 1 74 1
## 04:15:00 04:30:00 04:45:00 04:50:00 05:00:00 05:30:00 05:50:00 06:00:00
## 2 20 2 2 43 8 1 18
## 06:30:00 07:00:00 07:15:00 07:30:00 07:55:00 08:00:00 08:10:00 08:15:00
## 5 16 1 2 1 7 1 1
## 08:30:00 09:00:00 09:30:00 10:00:00 11:00:00 12:00:00 13:00:00 15:00:00
## 3 6 6 4 2 1 1 1
## 17:00:00 18:30:00
## 1 1
##
## 00:00:00 00:30:00 00:40:00 00:45:00 00:50:00 01:00:00 01:05:00 01:10:00
## 2020 0 0 0 0 0 3 0 0
## 2021 0 0 0 1 0 2 0 0
## 2022 0 1 0 0 0 3 1 1
## 2023 0 0 1 1 0 5 0 0
## 2024 0 0 1 0 2 1 1 0
##
## 01:30:00 01:35:00 01:40:00 01:45:00 02:00:00 02:01:00 02:10:00 02:15:00
## 2020 7 0 1 0 30 0 0 0
## 2021 4 0 0 0 10 0 0 0
## 2022 2 1 1 0 4 1 0 1
## 2023 14 0 1 2 18 0 1 3
## 2024 1 1 0 0 13 0 0 1
##
## 02:20:00 02:30:00 02:35:00 02:40:00 02:45:00 02:50:00 03:00:00 03:02:00
## 2020 0 3 1 0 0 0 18 0
## 2021 1 1 0 0 0 0 9 1
## 2022 0 2 0 0 1 0 5 0
## 2023 0 12 0 1 3 2 21 0
## 2024 0 3 0 0 0 0 13 0
##
## 03:15:00 03:20:00 03:30:00 03:36:00 03:45:00 03:50:00 04:00:00 04:10:00
## 2020 0 0 9 0 0 0 18 0
## 2021 0 0 4 0 0 0 7 0
## 2022 1 1 5 1 1 0 9 1
## 2023 3 0 17 0 1 1 26 0
## 2024 0 1 4 0 0 0 14 0
##
## 04:15:00 04:30:00 04:45:00 04:50:00 05:00:00 05:30:00 05:50:00 06:00:00
## 2020 0 2 0 0 7 1 0 0
## 2021 0 3 0 0 6 2 1 2
## 2022 1 5 0 0 8 2 0 6
## 2023 0 6 1 0 11 1 0 6
## 2024 1 3 1 2 11 2 0 4
##
## 06:30:00 07:00:00 07:15:00 07:30:00 07:55:00 08:00:00 08:10:00 08:15:00
## 2020 1 1 0 0 0 0 0 0
## 2021 2 5 1 0 0 3 0 0
## 2022 0 9 0 1 1 1 0 0
## 2023 2 0 0 1 0 3 0 1
## 2024 0 1 0 0 0 0 1 0
##
## 08:30:00 09:00:00 09:30:00 10:00:00 11:00:00 12:00:00 13:00:00 15:00:00
## 2020 0 0 0 0 0 0 0 0
## 2021 2 2 2 1 1 0 1 0
## 2022 0 3 1 1 1 1 0 1
## 2023 1 1 3 2 0 0 0 0
## 2024 0 0 0 0 0 0 0 0
##
## 17:00:00 18:30:00
## 2020 0 0
## 2021 0 0
## 2022 0 0
## 2023 1 1
## 2024 0 0
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
df. <- survey[, c("fiche_n", "a", "mod_peche", "age_moyen", "cat_pro", "nb_sort_an", "avis_pnm"
, "sexe"
, "dep_pdb", "dep_pe", "dep_csm", "dep_po"
, "res_tour"
, "espcib1", "espcib2", "espcib3"
, "we", "sem"
, "aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q"
, "z_1","z_2","z_3","z_4","z_6","z_7","z_8","z_9","z_54","z_55","z_56","z_57","z_58","z_59","z_60","z_61"
, "poss_bat"
, "Temps_peche_effectif"
, "Temps_peche_estime")]
unique(df.$poss_bat); length(na.omit(df.$poss_bat)) ; table(df.$poss_bat) ; table(df.$a, df.$poss_bat)
## [1] "non" "oui" "NA" NA
## [1] 509
##
## NA non oui
## 248 138 123
##
## NA non oui
## 2020 0 82 20
## 2021 0 25 49
## 2022 0 31 54
## 2023 174 0 0
## 2024 0 0 0
df.$poss_bat <- ifelse(df.$poss_bat == "NA", NA, df.$poss_bat)
unique(df.$poss_bat); length(na.omit(df.$poss_bat)) ; table(df.$poss_bat) ; table(df.$a, df.$poss_bat)
## [1] "non" "oui" NA
## [1] 261
##
## non oui
## 138 123
##
## non oui
## 2020 82 20
## 2021 25 49
## 2022 31 54
## 2023 0 0
## 2024 0 0
df. %>%
mutate(Temps_peche_effectif.30min = if_else(Temps_peche_effectif < parse_hms("00:30:00"), NA, as_hms(Temps_peche_effectif))) -> df.
df.$Temps_peche_effectif.cat2h <- NA
for (i in 1:length(df.$Temps_peche_effectif.30min)) {
#i=1
if (as.numeric(df.[i, "Temps_peche_effectif.30min"]) < as.numeric(as.hms("02:00:00")) & !is.na(df.[i, "Temps_peche_effectif.30min"])) {
df.[i, "Temps_peche_effectif.cat2h"] <- "<2h"
} else if (as.numeric(df.[i, "Temps_peche_effectif.30min"]) >= as.numeric(as.hms("02:00:00")) & !is.na(df.[i, "Temps_peche_effectif.30min"])) {
df.[i, "Temps_peche_effectif.cat2h"] <- ">=2h"
} else if (is.na(df.[i, "Temps_peche_effectif.30min"])) {
df.[i, "Temps_peche_effectif.cat2h"] <- NA
}
rm(i)
}
## Warning: `as.hms()` was deprecated in hms 0.5.0.
## ℹ Please use `as_hms()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
df. %>%
mutate(Temps_peche_estime.30min = if_else(Temps_peche_estime < parse_hms("00:30:00"), NA, as_hms(Temps_peche_estime))) -> df.
df.$Temps_peche_estime.cat2h <- NA
for (i in 1:length(df.$Temps_peche_estime.30min)) {
#i=1
if (as.numeric(df.[i, "Temps_peche_estime.30min"]) < as.numeric(as.hms("02:00:00")) & !is.na(df.[i, "Temps_peche_estime.30min"])) {
df.[i, "Temps_peche_estime.cat2h"] <- "<2h"
} else if (as.numeric(df.[i, "Temps_peche_estime.30min"]) >= as.numeric(as.hms("02:00:00")) & !is.na(df.[i, "Temps_peche_estime.30min"])) {
df.[i, "Temps_peche_estime.cat2h"] <- ">=2h"
} else if (is.na(df.[i, "Temps_peche_estime.30min"])) {
df.[i, "Temps_peche_estime.cat2h"] <- NA
}
rm(i)
}
unique(df.$Temps_peche_effectif.cat2h); length(na.omit(df.$Temps_peche_effectif.cat2h)) ; table(df.$Temps_peche_effectif.cat2h) ; table(df.$a, df.$Temps_peche_effectif.cat2h)
## [1] "<2h" ">=2h" NA
## [1] 474
##
## <2h >=2h
## 233 241
##
## <2h >=2h
## 2020 57 29
## 2021 25 41
## 2022 27 51
## 2023 81 83
## 2024 41 37
unique(df.$Temps_peche_estime.cat2h); length(na.omit(df.$Temps_peche_estime.cat2h)) ; table(df.$Temps_peche_estime.cat2h) ; table(df.$a, df.$Temps_peche_estime.cat2h)
## [1] ">=2h" "<2h" NA
## [1] 519
##
## <2h >=2h
## 60 459
##
## <2h >=2h
## 2020 11 91
## 2021 7 67
## 2022 10 75
## 2023 24 150
## 2024 7 75
df.time <- survey[, c("fiche_n","we", "sem")]
summary(df.time[,-1])
## we sem
## Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000
## Mean :0.1226 Mean :0.0651
## 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000
## NA's :509 NA's :509
replace_values <- function(column_name, data) {
if (column_name == "we") {
data[data == 1] <- "weekend"
} else if (column_name == "sem") {
data[data == 1] <- "semaine"
}
return(data)
}
cols_to_replace <- c("we", "sem")
df.time[cols_to_replace] <- lapply(cols_to_replace, function(col) replace_values(col, df.time[[col]]))
#write.csv2(df.spatial, "df.spatial.csv") #for ChatGPT
concatenate_unique <- function(row) {
values <- as.character(row)
values <- values[values != "0"]
unique_values <- unique(values)
paste(unique_values, collapse = ", ")
}
df.time <- df.time %>%
rowwise() %>%
mutate(concatenated_values = concatenate_unique(c_across(2:3)))
df.time <- data.frame(df.time)
for (i in 1:nrow(df.time)) {
df.time[i,"concatenated_values"] <- ifelse(df.time[i,"we"]=="0" & df.time[i,"sem"]=="0" & df.time[i,"concatenated_values"]=="", "0", df.time[i,"concatenated_values"])
}
df.time[,"concatenated_values"] <- ifelse(df.time[,"concatenated_values"] == "NA", NA, df.time[,"concatenated_values"] )
#df.time <- data.frame(df.time)
names(df.time)[names(df.time) == "concatenated_values"] <- "time.week"
table(df.time[,2:4])
## , , time.week = 0
##
## sem
## we 0 semaine
## 0 214 0
## weekend 0 0
##
## , , time.week = semaine
##
## sem
## we 0 semaine
## 0 0 15
## weekend 0 0
##
## , , time.week = weekend
##
## sem
## we 0 semaine
## 0 0 0
## weekend 30 0
##
## , , time.week = weekend, semaine
##
## sem
## we 0 semaine
## 0 0 0
## weekend 0 2
df. <- bind_cols(df., df.time[,c("fiche_n", "time.week")])
## New names:
## • `fiche_n` -> `fiche_n...1`
## • `fiche_n` -> `fiche_n...50`
df. <- subset(df., select = -c(fiche_n...50))
names(df.)[names(df.) == "fiche_n...1"] <- "fiche_n"
rm(df.time,i)
unique(df.$time.week); length(na.omit(df.$time.week)) ; table(df.$time.week) ; table(df.$a, df.$time.week)
## [1] "0" "weekend" "semaine" "weekend, semaine"
## [5] NA
## [1] 261
##
## 0 semaine weekend weekend, semaine
## 214 15 30 2
##
## 0 semaine weekend weekend, semaine
## 2020 101 0 1 0
## 2021 53 5 16 0
## 2022 60 10 13 2
## 2023 0 0 0 0
## 2024 0 0 0 0
# either some fishers do not fish neither the week, nor the weekend, either the 0 are in fact NAs !? consider them like NAs, otherwise a third category "03 that makes no sense. But then almost no observations, so removed from the analysis.
df.$time.week <- ifelse(df.$time.week == "0", NA, df.$time.week)
unique(df.$time.week); length(na.omit(df.$time.week)) ; table(df.$time.week) ; table(df.$a, df.$time.week)
## [1] NA "weekend" "semaine" "weekend, semaine"
## [1] 47
##
## semaine weekend weekend, semaine
## 15 30 2
##
## semaine weekend weekend, semaine
## 2020 0 1 0
## 2021 5 16 0
## 2022 10 13 2
## 2023 0 0 0
## 2024 0 0 0
df.time <- survey[, c("fiche_n","aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q")]
summary(df.time[,-1])
## aube matin soir crepuscule
## Min. :0.0000 Min. :0.000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :1.000 Median :0.000 Median :0.0000
## Mean :0.1801 Mean :0.705 Mean :0.069 Mean :0.0805
## 3rd Qu.:0.0000 3rd Qu.:1.000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.000 Max. :1.000 Max. :1.0000
## NA's :509 NA's :509 NA's :509 NA's :509
## nuit apm journee nimp_q
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.0421 Mean :0.0996 Mean :0.0383 Mean :0.0843
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :509 NA's :509 NA's :509 NA's :509
replace_values <- function(column_name, data) {
if (column_name == "aube") {
data[data == 1] <- "aube"
} else if (column_name == "matin") {
data[data == 1] <- "matin"
} else if (column_name == "soir") {
data[data == 1] <- "soir"
} else if (column_name == "crepuscule") {
data[data == 1] <- "crepuscule"
} else if (column_name == "nuit") {
data[data == 1] <- "nuit"
} else if (column_name == "apm") {
data[data == 1] <- "apm"
} else if (column_name == "journee") {
data[data == 1] <- "journee"
} else if (column_name == "nimp_q") {
data[data == 1] <- "nimp_q"
}
return(data)
}
cols_to_replace <- c("aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q")
df.time[cols_to_replace] <- lapply(cols_to_replace, function(col) replace_values(col, df.time[[col]]))
#write.csv2(df.spatial, "df.spatial.csv") #for ChatGPT
concatenate_unique <- function(row) {
values <- as.character(row)
values <- values[values != "0"]
unique_values <- unique(values)
paste(unique_values, collapse = ", ")
}
df.time <- df.time %>%
rowwise() %>%
mutate(concatenated_values = concatenate_unique(c_across(2:9)))
df.time <- data.frame(df.time)
for (i in 1:nrow(df.time)) {
df.time[i,"concatenated_values"] <- ifelse(
df.time[i,"aube"]=="0"
& df.time[i,"matin"]=="0"
& df.time[i,"soir"]=="0"
& df.time[i,"crepuscule"]=="0"
& df.time[i,"nuit"]=="0"
& df.time[i,"apm"]=="0"
& df.time[i,"journee"]=="0"
& df.time[i,"nimp_q"]=="0"
& df.time[i,"concatenated_values"]==""
, "0", df.time[i,"concatenated_values"])
}
df.time[,"concatenated_values"] <- ifelse(df.time[,"concatenated_values"] == "NA", NA, df.time[,"concatenated_values"] )
#df.time <- data.frame(df.time)
names(df.time)[names(df.time) == "concatenated_values"] <- "time.day"
table(df.time[,2:10])
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 1 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
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##
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##
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##
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##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
## matin
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
## matin
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##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
## matin
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
## matin
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##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
## matin
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##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
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## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
df. <- bind_cols(df., df.time[,c("fiche_n", "time.day")])
## New names:
## • `fiche_n` -> `fiche_n...1`
## • `fiche_n` -> `fiche_n...51`
df. <- subset(df., select = -c(fiche_n...51))
names(df.)[names(df.) == "fiche_n...1"] <- "fiche_n"
rm(df.time,i)
unique(df.$time.day); length(na.omit(df.$time.day)) ; table(df.$time.day) ; table(df.$a, df.$time.day)
## [1] "matin" "soir"
## [3] "crepuscule" "matin, nuit"
## [5] "aube" "matin, journee"
## [7] "0" "matin, crepuscule"
## [9] "matin, crepuscule, apm" "matin, apm"
## [11] "journee" "aube, matin"
## [13] "aube, matin, apm" "matin, crepuscule, nuit"
## [15] "crepuscule, apm" "apm"
## [17] "nimp_q" "aube, matin, crepuscule"
## [19] "aube, matin, nuit" "crepuscule, nuit, apm"
## [21] "nuit" "aube, matin, crepuscule, apm"
## [23] "aube, crepuscule" "aube, nuit"
## [25] "matin, soir, crepuscule, nuit" NA
## [1] 261
##
## 0 apm
## 1 3
## aube aube, crepuscule
## 9 1
## aube, matin aube, matin, apm
## 27 5
## aube, matin, crepuscule aube, matin, crepuscule, apm
## 1 1
## aube, matin, nuit aube, nuit
## 2 1
## crepuscule crepuscule, apm
## 11 1
## crepuscule, nuit, apm journee
## 1 9
## matin matin, apm
## 125 13
## matin, crepuscule matin, crepuscule, apm
## 1 2
## matin, crepuscule, nuit matin, journee
## 1 1
## matin, nuit matin, soir, crepuscule, nuit
## 4 1
## nimp_q nuit
## 22 1
## soir
## 17
##
## 0 apm aube aube, crepuscule aube, matin aube, matin, apm
## 2020 0 0 0 0 0 0
## 2021 1 1 4 0 10 1
## 2022 0 2 5 1 17 4
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## aube, matin, crepuscule aube, matin, crepuscule, apm aube, matin, nuit
## 2020 0 0 0
## 2021 0 0 0
## 2022 1 1 2
## 2023 0 0 0
## 2024 0 0 0
##
## aube, nuit crepuscule crepuscule, apm crepuscule, nuit, apm journee
## 2020 0 7 0 0 0
## 2021 0 2 1 0 9
## 2022 1 2 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## matin matin, apm matin, crepuscule matin, crepuscule, apm
## 2020 78 0 0 0
## 2021 24 12 1 1
## 2022 23 1 0 1
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## matin, crepuscule, nuit matin, journee matin, nuit
## 2020 0 0 0
## 2021 1 1 4
## 2022 0 0 0
## 2023 0 0 0
## 2024 0 0 0
##
## matin, soir, crepuscule, nuit nimp_q nuit soir
## 2020 0 0 0 17
## 2021 0 1 0 0
## 2022 1 21 1 0
## 2023 0 0 0 0
## 2024 0 0 0 0
df.$time.day.gp <- df.$time.day
df.$time.day.gp <- ifelse(df.$time.day.gp %in% c("aube", "matin"), "am", df.$time.day.gp)
df.$time.day.gp <- ifelse(df.$time.day.gp %in% c("apm", "crepuscule", "soir"), "pm", df.$time.day.gp)
df.$time.day.gp <- ifelse(df.$time.day.gp %notin% c("0", "NA",
"am", "pm", "nuit", "journee", "nimp_q")
& !is.na(df.$time.day.gp), "nimp_q", df.$time.day.gp)
unique(df.$time.day.gp); length(na.omit(df.$time.day.gp)) ; table(df.$time.day.gp) ; table(df.$a, df.$time.day.gp)
## [1] "am" "pm" "nimp_q" "0" "journee" "nuit" NA
## [1] 261
##
## 0 am journee nimp_q nuit pm
## 1 134 9 85 1 31
##
## 0 am journee nimp_q nuit pm
## 2020 0 78 0 0 0 24
## 2021 1 28 9 33 0 3
## 2022 0 28 0 52 1 4
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
# remove the variable level "0" that makes no sense
df.$time.day.gp <- ifelse(df.$time.day.gp == "0", NA, df.$time.day.gp)
unique(df.$time.day.gp); length(na.omit(df.$time.day.gp)) ; table(df.$time.day.gp) ; table(df.$a, df.$time.day.gp)
## [1] "am" "pm" "nimp_q" NA "journee" "nuit"
## [1] 260
##
## am journee nimp_q nuit pm
## 134 9 85 1 31
##
## am journee nimp_q nuit pm
## 2020 78 0 0 0 24
## 2021 28 9 33 0 3
## 2022 28 0 52 1 4
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
df.spatial <- survey[, c("fiche_n","z_1","z_2","z_3","z_4","z_6","z_7","z_8","z_9","z_54","z_55","z_56","z_57","z_58","z_59","z_60","z_61")]
summary(df.spatial[,-1])
## z_1 z_2 z_3 z_4
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.1786 Mean :0.1935 Mean :0.146 Mean :0.1749
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## NA's :182 NA's :181 NA's :181 NA's :181
## z_6 z_7 z_8 z_9
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2139 Mean :0.3345 Mean :0.2326 Mean :0.3192
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :9.0000
## NA's :181 NA's :181 NA's :181 NA's :181
## z_54 z_55 z_56 z_57
## Min. :0.00000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.00000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.05433 Mean :0.0798 Mean :0.107 Mean :0.1188
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.0000 Max. :1.000 Max. :1.0000
## NA's :181 NA's :181 NA's :181 NA's :181
## z_58 z_59 z_60 z_61
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1749 Mean :0.3939 Mean :0.1902 Mean :0.1783
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :181 NA's :181 NA's :181 NA's :181
table(df.spatial$z_9)
##
## 0 1 9
## 409 179 1
df.spatial$z_9 <- ifelse(df.spatial$z_9 == 9, 1, df.spatial$z_9)
#write.csv2(df.spatial, "df.spatial.csv") #for ChatGPT
replace_values <- function(column_name, data) {
if (column_name %in% c("z_54", "z_55", "z_56", "z_57", "z_58")) {
data[data == 1] <- "Agriates"
} else if (column_name == "z_59") {
data[data == 1] <- "Saint-Florent"
} else if (column_name %in% c("z_60", "z_61", "z_1", "z_2")) {
data[data == 1] <- "Ouest Cap"
} else if (column_name %in% c("z_3", "z_4")) {
data[data == 1] <- "Nord Cap"
} else if (column_name %in% c("z_6", "z_7", "z_8", "z_9")) {
data[data == 1] <- "Est Cap"
}
return(data)
}
cols_to_replace <- c("z_54", "z_55", "z_56", "z_57", "z_58", "z_59", "z_60", "z_61", "z_1", "z_2", "z_3", "z_4", "z_6", "z_7", "z_8", "z_9")
df.spatial[cols_to_replace] <- lapply(cols_to_replace, function(col) replace_values(col, df.spatial[[col]]))
#write.csv2(df.spatial, "df.spatial.csv") #for ChatGPT
concatenate_unique <- function(row) {
values <- as.character(row)
values <- values[values != "0"]
unique_values <- unique(values)
paste(unique_values, collapse = ", ")
}
df.spatial <- df.spatial %>%
rowwise() %>%
mutate(concatenated_values = concatenate_unique(c_across(2:17)))
df.spatial <- data.frame(df.spatial)
names(df.spatial)[names(df.spatial) == "concatenated_values"] <- "zone"
df. <- bind_cols(df., df.spatial[,c("fiche_n", "zone")])
## New names:
## • `fiche_n` -> `fiche_n...1`
## • `fiche_n` -> `fiche_n...53`
df. <- subset(df., select = -c(fiche_n...53))
names(df.)[names(df.) == "fiche_n...1"] <- "fiche_n"
rm(df.spatial)
unique(df.$zone); length(na.omit(df.$zone)) ; table(df.$zone) ; table(df.$a, df.$zone)
## [1] "Est Cap"
## [2] "Saint-Florent"
## [3] "Ouest Cap"
## [4] "Ouest Cap, Nord Cap, Est Cap, Saint-Florent"
## [5] "Ouest Cap, Nord Cap, Est Cap"
## [6] "Ouest Cap, Est Cap, Saint-Florent"
## [7] "Ouest Cap, Nord Cap"
## [8] "Ouest Cap, Agriates, Saint-Florent"
## [9] "Ouest Cap, Est Cap, Agriates, Saint-Florent"
## [10] "Ouest Cap, Nord Cap, Agriates, Saint-Florent"
## [11] "Agriates, Saint-Florent, Ouest Cap"
## [12] "Nord Cap, Ouest Cap"
## [13] "Est Cap, Saint-Florent"
## [14] "Ouest Cap, Nord Cap, Est Cap, Agriates, Saint-Florent"
## [15] "Agriates, Saint-Florent"
## [16] "Agriates"
## [17] "Nord Cap, Est Cap"
## [18] "Ouest Cap, Agriates"
## [19] "Nord Cap"
## [20] "Saint-Florent, Ouest Cap"
## [21] "Ouest Cap, Est Cap"
## [22] "Est Cap, Agriates, Saint-Florent"
## [23] "Ouest Cap, Saint-Florent"
## [24] "Agriates, Ouest Cap"
## [25] "NA"
## [26] "Ouest Cap, Nord Cap, Est Cap, Agriates"
## [27] "NA, Nord Cap, Est Cap"
## [28] "Est Cap, Saint-Florent, Ouest Cap"
## [29] "Nord Cap, Est Cap, Saint-Florent, Ouest Cap"
## [30] "Ouest Cap, Est Cap, Agriates"
## [31] "Est Cap, Ouest Cap"
## [32] "Nord Cap, Est Cap, Agriates, Saint-Florent"
## [33] "Est Cap, Agriates, Saint-Florent, Ouest Cap"
## [1] 770
##
## Agriates
## 10
## Agriates, Ouest Cap
## 2
## Agriates, Saint-Florent
## 13
## Agriates, Saint-Florent, Ouest Cap
## 27
## Est Cap
## 217
## Est Cap, Agriates, Saint-Florent
## 8
## Est Cap, Agriates, Saint-Florent, Ouest Cap
## 1
## Est Cap, Ouest Cap
## 1
## Est Cap, Saint-Florent
## 14
## Est Cap, Saint-Florent, Ouest Cap
## 1
## NA
## 181
## NA, Nord Cap, Est Cap
## 1
## Nord Cap
## 10
## Nord Cap, Est Cap
## 26
## Nord Cap, Est Cap, Agriates, Saint-Florent
## 1
## Nord Cap, Est Cap, Saint-Florent, Ouest Cap
## 1
## Nord Cap, Ouest Cap
## 1
## Ouest Cap
## 38
## Ouest Cap, Agriates
## 5
## Ouest Cap, Agriates, Saint-Florent
## 14
## Ouest Cap, Est Cap
## 8
## Ouest Cap, Est Cap, Agriates
## 1
## Ouest Cap, Est Cap, Agriates, Saint-Florent
## 4
## Ouest Cap, Est Cap, Saint-Florent
## 4
## Ouest Cap, Nord Cap
## 16
## Ouest Cap, Nord Cap, Agriates, Saint-Florent
## 6
## Ouest Cap, Nord Cap, Est Cap
## 19
## Ouest Cap, Nord Cap, Est Cap, Agriates
## 2
## Ouest Cap, Nord Cap, Est Cap, Agriates, Saint-Florent
## 27
## Ouest Cap, Nord Cap, Est Cap, Saint-Florent
## 8
## Ouest Cap, Saint-Florent
## 7
## Saint-Florent
## 89
## Saint-Florent, Ouest Cap
## 7
##
## Agriates Agriates, Ouest Cap Agriates, Saint-Florent
## 2020 0 0 0
## 2021 3 0 2
## 2022 2 1 7
## 2023 1 1 1
## 2024 1 0 3
##
## Agriates, Saint-Florent, Ouest Cap Est Cap
## 2020 0 73
## 2021 10 24
## 2022 9 17
## 2023 2 80
## 2024 6 18
##
## Est Cap, Agriates, Saint-Florent
## 2020 0
## 2021 0
## 2022 3
## 2023 4
## 2024 0
##
## Est Cap, Agriates, Saint-Florent, Ouest Cap Est Cap, Ouest Cap
## 2020 0 0
## 2021 0 0
## 2022 0 0
## 2023 0 0
## 2024 0 1
##
## Est Cap, Saint-Florent Est Cap, Saint-Florent, Ouest Cap NA
## 2020 0 0 0
## 2021 2 0 0
## 2022 0 0 0
## 2023 7 1 1
## 2024 3 0 0
##
## NA, Nord Cap, Est Cap Nord Cap Nord Cap, Est Cap
## 2020 0 0 0
## 2021 0 1 1
## 2022 0 4 2
## 2023 1 1 16
## 2024 0 1 0
##
## Nord Cap, Est Cap, Agriates, Saint-Florent
## 2020 0
## 2021 0
## 2022 0
## 2023 0
## 2024 0
##
## Nord Cap, Est Cap, Saint-Florent, Ouest Cap Nord Cap, Ouest Cap
## 2020 0 0
## 2021 0 1
## 2022 0 0
## 2023 1 0
## 2024 0 0
##
## Ouest Cap Ouest Cap, Agriates Ouest Cap, Agriates, Saint-Florent
## 2020 7 0 0
## 2021 9 1 4
## 2022 9 4 5
## 2023 3 0 2
## 2024 1 0 1
##
## Ouest Cap, Est Cap Ouest Cap, Est Cap, Agriates
## 2020 0 0
## 2021 0 0
## 2022 3 0
## 2023 3 0
## 2024 0 1
##
## Ouest Cap, Est Cap, Agriates, Saint-Florent
## 2020 0
## 2021 1
## 2022 0
## 2023 0
## 2024 0
##
## Ouest Cap, Est Cap, Saint-Florent Ouest Cap, Nord Cap
## 2020 0 0
## 2021 1 2
## 2022 2 3
## 2023 1 1
## 2024 0 0
##
## Ouest Cap, Nord Cap, Agriates, Saint-Florent
## 2020 0
## 2021 3
## 2022 2
## 2023 0
## 2024 0
##
## Ouest Cap, Nord Cap, Est Cap Ouest Cap, Nord Cap, Est Cap, Agriates
## 2020 1 0
## 2021 1 0
## 2022 2 0
## 2023 5 1
## 2024 0 0
##
## Ouest Cap, Nord Cap, Est Cap, Agriates, Saint-Florent
## 2020 0
## 2021 3
## 2022 1
## 2023 12
## 2024 0
##
## Ouest Cap, Nord Cap, Est Cap, Saint-Florent Ouest Cap, Saint-Florent
## 2020 1 0
## 2021 0 0
## 2022 0 3
## 2023 6 2
## 2024 1 2
##
## Saint-Florent Saint-Florent, Ouest Cap
## 2020 20 0
## 2021 4 1
## 2022 4 2
## 2023 19 2
## 2024 41 2
df.$zone.gp <- df.$zone
df.$zone.gp <- ifelse(df.$zone.gp %notin% c("0", "NA",
"Est Cap", "Ouest Cap", "Nord Cap", "Saint-Florent", "Agriates")
& !is.na(df.$zone.gp), "nimp_ou", df.$zone.gp)
unique(df.$zone.gp); length(na.omit(df.$zone.gp)) ; table(df.$zone.gp) ; table(df.$a, df.$zone.gp)
## [1] "Est Cap" "Saint-Florent" "Ouest Cap" "nimp_ou"
## [5] "Agriates" "Nord Cap" "NA"
## [1] 770
##
## Agriates Est Cap NA nimp_ou Nord Cap
## 10 217 181 225 10
## Ouest Cap Saint-Florent
## 38 89
##
## Agriates Est Cap NA nimp_ou Nord Cap Ouest Cap Saint-Florent
## 2020 0 73 0 2 0 7 20
## 2021 3 24 0 33 1 9 4
## 2022 2 17 0 49 4 9 4
## 2023 1 80 1 69 1 3 19
## 2024 1 18 0 20 1 1 41
df.$zone.gp <- ifelse(df.$zone.gp == "NA", NA, df.$zone.gp)
unique(df.$zone.gp); length(na.omit(df.$zone.gp)) ; table(df.$zone.gp) ; table(df.$a, df.$zone.gp)
## [1] "Est Cap" "Saint-Florent" "Ouest Cap" "nimp_ou"
## [5] "Agriates" "Nord Cap" NA
## [1] 589
##
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 10 217 225 10 38
## Saint-Florent
## 89
##
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap Saint-Florent
## 2020 0 73 2 0 7 20
## 2021 3 24 33 1 9 4
## 2022 2 17 49 4 9 4
## 2023 1 80 69 1 3 19
## 2024 1 18 20 1 1 41
df. <- add_column(df., age_classe = NA, .after = "age_moyen")
df.$age_classe <- as.character(df.$age_classe)
df. <- data.frame(df.)
df.$age_classe <- ifelse(df.$age_moyen >= 70, "70 et plus", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 60 & df.$age_moyen < 70, "60-69", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 50 & df.$age_moyen < 60, "50-59", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 40 & df.$age_moyen < 50, "40-49", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen >= 25 & df.$age_moyen < 40, "25-39", df.$age_classe)
df.$age_classe <- ifelse(df.$age_moyen < 25, "13-24", df.$age_classe)
unique(df.$age_classe)
## [1] "50-59" "40-49" "25-39" "13-24" "60-69"
## [6] "70 et plus" NA
nrow(df.) ; length(na.omit(df.$age_classe))
## [1] 770
## [1] 331
unique(df.$age_classe); length(na.omit(df.$age_classe)) ; table(df.$age_classe) ; table(df.$a, df.$age_classe)
## [1] "50-59" "40-49" "25-39" "13-24" "60-69"
## [6] "70 et plus" NA
## [1] 331
##
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 17 53 72 128 36 25
##
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 2020 2 13 28 59 0 0
## 2021 0 16 14 42 1 1
## 2022 3 11 19 15 21 15
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
#we have no info about age_moyen in 2023 so not possible to plot the multivariate analysis, or we do not consider that variable neither in the analysis
df. %>% filter(mod_peche != "pdb, csm") -> df.
table(df.$mod_peche)
##
## csm pdb pe po
## 38 326 151 2
df.$mod_peche <- ifelse(df.$mod_peche == "csm", "chasse sous-marine", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pdb", "peche du bord", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pe", "peche embarquée", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "po", "peche à l'oursin", df.$mod_peche)
table(df.$mod_peche)
##
## chasse sous-marine peche à l'oursin peche du bord peche embarquée
## 38 2 326 151
df.$mod_peche <- as.factor(df.$mod_peche)
df.$mod_peche <- factor(df.$mod_peche, levels = c("chasse sous-marine", "peche du bord", "peche embarquée", "peche à l'oursin"))
table(df.$mod_peche)
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 38 326 151 2
nrow(df.) ; length(na.omit(df.$mod_peche))
## [1] 517
## [1] 517
unique(df.$mod_peche); length(na.omit(df.$mod_peche)) ; table(df.$mod_peche) ; table(df.$a, df.$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## 4 Levels: chasse sous-marine peche du bord ... peche à l'oursin
## [1] 517
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 38 326 151 2
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 2020 11 67 24 0
## 2021 2 21 50 1
## 2022 3 29 52 1
## 2023 21 131 20 0
## 2024 1 76 5 0
unique(df.$cat_pro)
## [1] "activite" "retraite" "sans_emploi" "etudiant" "NA"
## [6] "en_arret" NA
df.$cat_pro <- ifelse(df.$cat_pro == "NA", NA, df.$cat_pro)
table(df.$cat_pro)
##
## activite en_arret etudiant retraite sans_emploi
## 134 3 4 98 21
nrow(df.) ; length(na.omit(df.$cat_pro))
## [1] 517
## [1] 260
table(df.[, c("a", "cat_pro")])
## cat_pro
## a activite en_arret etudiant retraite sans_emploi
## 2020 40 0 1 45 16
## 2021 47 1 0 23 2
## 2022 47 2 3 30 3
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
df.$cat_pro.gp <- df.$cat_pro
df.$cat_pro.gp <- ifelse(df.$cat_pro.gp %in% c("sans_emploi", "en_arret"), "sans_emploi-en_arret", df.$cat_pro.gp)
table(df.$cat_pro.gp)
##
## activite etudiant retraite
## 134 4 98
## sans_emploi-en_arret
## 24
unique(df.$cat_pro.gp); length(na.omit(df.$cat_pro.gp)) ; table(df.$cat_pro.gp) ; table(df.$a, df.$cat_pro.gp)
## [1] "activite" "retraite" "sans_emploi-en_arret"
## [4] "etudiant" NA
## [1] 260
##
## activite etudiant retraite
## 134 4 98
## sans_emploi-en_arret
## 24
##
## activite etudiant retraite sans_emploi-en_arret
## 2020 40 1 45 16
## 2021 47 0 23 3
## 2022 47 3 30 5
## 2023 0 0 0 0
## 2024 0 0 0 0
table(survey[, c("a", "act_pro")])
## act_pro
## a activite agent commercial agent entretien mairie Oletta agent immobilier
## 2020 0 0 0 0
## 2021 0 0 0 0
## 2022 0 1 1 1
## 2023 0 0 0 0
## 2024 0 0 0 0
## act_pro
## a agent OFB Agent_entretien Agent_securite Agent_territorial_ Agriculteur
## 2020 0 1 1 0 1
## 2021 0 0 0 1 0
## 2022 1 0 0 0 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
## act_pro
## a Aide_soignant Architecte artisan artisan peintre
## 2020 1 0 0 0
## 2021 1 1 4 0
## 2022 0 0 3 1
## 2023 0 0 0 0
## 2024 0 0 0 0
## act_pro
## a Artisan(e)s,_commerçant(e)s_et_chef(fe)_d'entreprises Artisan_
## 2020 4 0
## 2021 0 2
## 2022 0 0
## 2023 0 0
## 2024 0 0
## act_pro
## a Assurance_ banquier Banquier Boucher boulanger
## 2020 0 0 0 1 0
## 2021 1 0 1 0 0
## 2022 0 1 0 0 1
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
## act_pro
## a Cadre_dans_l'environnement
## 2020 0
## 2021 1
## 2022 0
## 2023 0
## 2024 0
## act_pro
## a Cadres_et_profession_intellectuelles_superieures CC de Saint-Florent
## 2020 2 0
## 2021 0 0
## 2022 0 1
## 2023 0 0
## 2024 0 0
## act_pro
## a chauffeur chef d'entreprise Chef_d'entreprise chomeur Chomeur commerçant
## 2020 0 0 2 0 1 0
## 2021 0 1 0 1 0 2
## 2022 1 1 0 0 0 0
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
## act_pro
## a Commerçant Commerçant_ commercial Comptable Conducteur couvreur ebeniste
## 2020 0 0 0 1 0 0 0
## 2021 1 1 1 1 1 0 1
## 2022 0 0 2 0 0 1 0
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
## act_pro
## a Electricien employe employe au port employe office HLM Employe(e)s
## 2020 1 0 0 0 1
## 2021 1 1 1 0 0
## 2022 0 0 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
## act_pro
## a Enseignant Enseignante entrepreneur etudiant Etudiant fonctionnaire
## 2020 1 1 0 0 1 0
## 2021 0 0 0 0 0 2
## 2022 0 0 1 0 0 3
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
## act_pro
## a garde_forestier gardien gent de terrain PNMCCA geometre
## 2020 0 0 0 0
## 2021 0 1 0 0
## 2022 1 0 1 1
## 2023 0 0 0 0
## 2024 0 0 0 0
## act_pro
## a Gerant_de_societe infirmier Infirmier Informaticien ingenieur Ingenieur
## 2020 0 0 2 1 0 1
## 2021 1 0 0 0 1 0
## 2022 0 1 0 0 0 0
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
## act_pro
## a Ingenieur_ Ingenieur_en_aquaculture Kinesitherapeute livreur Livreur
## 2020 0 0 1 0 2
## 2021 1 1 0 0 0
## 2022 0 0 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
## act_pro
## a location bateaux Location_de_gîtes lyceen maçon Maçon Magasinier manager
## 2020 0 0 0 0 2 1 0
## 2021 0 1 0 1 0 0 0
## 2022 1 0 1 0 0 0 1
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
## act_pro
## a Marayeur marin marin commerce medecin menuisier moniteur de peche nA
## 2020 0 0 0 0 0 0 0
## 2021 1 0 1 1 0 1 0
## 2022 0 3 0 0 1 0 1
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
## act_pro
## a NA ouvrier paysagiste Peintre plombier Policier_aux_frontieres Pompier
## 2020 0 0 0 3 0 1 0
## 2021 2 0 0 0 1 0 1
## 2022 19 1 3 0 1 0 0
## 2023 174 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
## act_pro
## a professeur professeur de tennis Reparateur_electromenager
## 2020 0 0 1
## 2021 0 0 0
## 2022 1 1 0
## 2023 0 0 0
## 2024 0 0 0
## act_pro
## a Responsable_securite restaurateur Restaurateur restauration retraire
## 2020 1 0 1 0 0
## 2021 0 2 2 0 1
## 2022 0 1 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
## act_pro
## a retraite Retraite Retraite(e)s Retraite_ sans emploi sans_emploi
## 2020 0 44 1 0 0 0
## 2021 12 7 0 2 1 0
## 2022 18 0 0 0 0 1
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
## act_pro
## a Sans_emploi serrurier Tatoueur Taxi technicien Technicien Terrassier
## 2020 16 0 1 0 0 0 0
## 2021 1 0 0 1 0 1 1
## 2022 0 1 0 0 1 0 0
## 2023 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0
## act_pro
## a transition transporteur de fond Vendeur Vendeur_de_materiel_de_peche
## 2020 0 0 1 0
## 2021 0 0 0 1
## 2022 1 1 0 0
## 2023 0 0 0 0
## 2024 0 0 0 0
## act_pro
## a Vendeuse Vigneron
## 2020 1 1
## 2021 0 0
## 2022 0 0
## 2023 0 0
## 2024 0 0
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
unique(filter(survey[,c("a", "act_pro")], "a" == "2023"))
## # A tibble: 0 × 2
## # ℹ 2 variables: a <chr>, act_pro <chr>
#we have no info about cat_pro in 2023 so not possible to plot the multivariate analysis, or we do not consider that variable neither in the analysis; idem for act_pro
unique(df.$avis_pnm)
## [1] "p_avis" "t_positif" "positif" "nsp" "_" "negatif"
## [7] "t_negatif" "NA" NA
df. <- add_column(df., classe_avis_pnm = df.$avis_pnm, .after = "avis_pnm")
unique(df.$classe_avis_pnm)
## [1] "p_avis" "t_positif" "positif" "nsp" "_" "negatif"
## [7] "t_negatif" "NA" NA
df.$classe_avis_pnm <- ifelse(df.$classe_avis_pnm == "NA", NA, df.$classe_avis_pnm)
df.$classe_avis_pnm <- ifelse(df.$classe_avis_pnm == "_", NA, df.$classe_avis_pnm)
df.$classe_avis_pnm <- ifelse(df.$classe_avis_pnm == "t_positif", "positif", df.$classe_avis_pnm)
df.$classe_avis_pnm <- ifelse(df.$classe_avis_pnm == "t_negatif", "negatif", df.$classe_avis_pnm)
df.$classe_avis_pnm <- ifelse(df.$classe_avis_pnm == "nsp", "p_avis", df.$classe_avis_pnm)
table(df.$classe_avis_pnm)
##
## negatif p_avis positif
## 2 40 218
unique(df.$classe_avis_pnm); length(na.omit(df.$classe_avis_pnm)) ; table(df.$classe_avis_pnm) ; table(df.$a, df.$classe_avis_pnm)
## [1] "p_avis" "positif" NA "negatif"
## [1] 260
##
## negatif p_avis positif
## 2 40 218
##
## negatif p_avis positif
## 2020 0 16 86
## 2021 0 6 67
## 2022 2 18 65
## 2023 0 0 0
## 2024 0 0 0
unique(df.$nb_sort_an)
## [1] "5" "30" "15" "40" "0" "10"
## [7] "1" "50" "64" "48" "80" "20"
## [13] "illimite" "150" "24" "130" "52" "100"
## [19] "25" "4" "60" "12" "2" "22"
## [25] "NA" NA
df.$nb_sort_an <- ifelse(df.$nb_sort_an == "NA", NA, df.$nb_sort_an)
df.$nb_sort_an <- ifelse(df.$nb_sort_an == "illimite", 999, df.$nb_sort_an)
table(df.$nb_sort_an) #or considering that variable as categorial, cfr idem classe_age?
##
## 0 1 10 100 12 130 15 150 2 20 22 24 25 30 4 40 48 5 50 52
## 2 7 12 4 3 1 76 1 2 9 1 2 1 40 3 27 1 44 8 1
## 60 64 80 999
## 2 1 1 12
nrow(df.) ; length(na.omit(df.$nb_sort_an))
## [1] 517
## [1] 261
unique(filter(survey[,c("a", "nb_sort_an")], "a" == "2023"))
## # A tibble: 0 × 2
## # ℹ 2 variables: a <chr>, nb_sort_an <chr>
#we have no info about nb_sort_an in 2023 so not possible to plot the multivariate analysis, or we do not consider that variable neither in the analysis; idem for act_pro
unique(df.$nb_sort_an); length(na.omit(df.$nb_sort_an)) ; table(df.$nb_sort_an) ; table(df.$a, df.$nb_sort_an) #no data for 2023
## [1] "5" "30" "15" "40" "0" "10" "1" "50" "64" "48" "80" "20"
## [13] "999" "150" "24" "130" "52" "100" "25" "4" "60" "12" "2" "22"
## [25] NA
## [1] 261
##
## 0 1 10 100 12 130 15 150 2 20 22 24 25 30 4 40 48 5 50 52
## 2 7 12 4 3 1 76 1 2 9 1 2 1 40 3 27 1 44 8 1
## 60 64 80 999
## 2 1 1 12
##
## 0 1 10 100 12 130 15 150 2 20 22 24 25 30 4 40 48 5 50 52 60 64 80
## 2020 1 0 0 0 0 0 59 0 0 0 0 0 0 8 0 1 0 33 0 0 0 0 0
## 2021 0 1 1 0 0 0 13 0 0 0 0 0 0 21 0 24 1 10 1 0 0 1 1
## 2022 1 6 11 4 3 1 4 1 2 9 1 2 1 11 3 2 0 1 7 1 2 0 0
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## 999
## 2020 0
## 2021 0
## 2022 12
## 2023 0
## 2024 0
df.$nb_sort_an <- as.numeric(df.$nb_sort_an)
df.$nb_sort_an_cat <- cut(df.$nb_sort_an, breaks=quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T), include.lowest=TRUE, labels=c(
paste0("Q1 (<=",
#quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[1]], "-",
quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[2]],
")") ,
paste0("Q2 (", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[2]]+1, "-", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[3]], ")") ,
paste0("Q3 (", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[3]]+1, "-", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[4]], ")") ,
paste0("Q4 (>=", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[4]]+1
#, "-", quantile(df.$nb_sort_an, probs=0:4/4, na.rm = T)[[5]]
,")") ))
unique(df.$nb_sort_an_cat); length(na.omit(df.$nb_sort_an_cat)) ; table(df.$nb_sort_an_cat) ; table(df.$a, df.$nb_sort_an_cat) #no data for 2023
## [1] Q1 (<=10) Q3 (16-30) Q2 (11-15) Q4 (>=31) <NA>
## Levels: Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## [1] 261
##
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 70 79 53 59
##
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 2020 34 59 8 1
## 2021 12 13 21 28
## 2022 24 7 24 30
## 2023 0 0 0 0
## 2024 0 0 0 0
# dépenses
# 1= "< 100 euros"; 2="entre 100-500 euros"; 3= "entre 500-1000 euros "; 4= "entre 1000-2000 euros ";5 ="supérieur à 2000"
table(df.$dep_pdb)
##
## 0 1 2 3 4 5 NA
## 135 74 35 14 1 2 174
table(df.$dep_pe)
##
## 0 1 2 3 4 5 NA
## 135 16 22 15 23 50 174
table(df.$dep_csm)
##
## 0 1 2 3 4 5 NA
## 232 9 13 3 3 1 174
table(df.$dep_po)
##
## 0 1 NA
## 256 5 174
df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")] <- lapply(df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], as.numeric)
## Warning in lapply(df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")],
## as.numeric): NAs introduits lors de la conversion automatique
## Warning in lapply(df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")],
## as.numeric): NAs introduits lors de la conversion automatique
## Warning in lapply(df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")],
## as.numeric): NAs introduits lors de la conversion automatique
## Warning in lapply(df.[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")],
## as.numeric): NAs introduits lors de la conversion automatique
df.$dep <- NA
df.$dep.median <- NA
df.$dep.median.rd <- NA
df.$dep_n <- NA
for (i in 1:nrow(df.)) {
#i=1
dep. <- as.vector(unlist(df.[i, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")]))
sort(dep.[na.omit(dep.)!=0])
df.[i,"dep"] <- paste0(sort(dep.[na.omit(dep.)!=0]), collapse=",")
df.[i,"dep.median"] <- median(dep.[na.omit(dep.)!=0])
df.[i,"dep.median.rd"] <- ceiling(df.[i,"dep.median"])
df.[i,"dep_n"] <- length(na.omit(dep.[dep.!=0]))
}
rm(dep.,i)
table(df.$dep)
##
## 1 1,1 1,1,1,2 1,2 1,3 1,4 1,5 2 2,2
## 257 88 3 1 3 2 1 1 51 5
## 2,3 2,5 3 3,5 4 4,4 5 5,5
## 1 4 28 1 24 1 45 1
arrange(unique(df.[, c("mod_peche", "dep_pdb", "dep_pe", "dep_csm", "dep_po")]), mod_peche)
## mod_peche dep_pdb dep_pe dep_csm dep_po
## 1 chasse sous-marine 0 0 1 0
## 2 chasse sous-marine 0 0 2 0
## 3 chasse sous-marine 0 0 4 0
## 4 chasse sous-marine 0 0 3 0
## 5 chasse sous-marine NA NA NA NA
## 6 peche du bord 2 0 0 0
## 7 peche du bord 1 0 0 0
## 8 peche du bord 4 0 0 0
## 9 peche du bord 3 0 0 0
## 10 peche du bord 1 0 0 1
## 11 peche du bord 5 0 0 0
## 12 peche du bord 1 0 1 0
## 13 peche du bord 2 5 0 0
## 14 peche du bord 2 0 1 0
## 15 peche du bord 3 0 2 0
## 16 peche du bord 1 3 0 0
## 17 peche du bord 2 0 2 0
## 18 peche du bord 2 2 0 0
## 19 peche du bord NA NA NA NA
## 20 peche embarquée 0 3 0 0
## 21 peche embarquée 0 4 0 0
## 22 peche embarquée 0 1 0 0
## 23 peche embarquée 0 5 0 0
## 24 peche embarquée 0 0 0 0
## 25 peche embarquée 0 2 0 0
## 26 peche embarquée 3 0 0 0
## 27 peche embarquée 0 5 0 1
## 28 peche embarquée 2 5 0 0
## 29 peche embarquée 0 5 2 0
## 30 peche embarquée 1 3 0 0
## 31 peche embarquée 3 5 0 0
## 32 peche embarquée 2 2 0 0
## 33 peche embarquée 2 0 0 0
## 34 peche embarquée 1 2 1 1
## 35 peche embarquée 0 4 4 0
## 36 peche embarquée 0 1 1 0
## 37 peche embarquée 0 5 5 0
## 38 peche embarquée NA NA NA NA
## 39 peche à l'oursin 0 0 4 1
## 40 peche à l'oursin 0 0 2 1
table(df.$dep.median.rd)
##
## 1 2 3 4 5
## 92 61 31 30 46
df.$dep.mod_peche <- NA
unique(df.$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## 4 Levels: chasse sous-marine peche du bord ... peche à l'oursin
for (i in 1:nrow(df.)) {
if(df.[i,"mod_peche"] == "peche du bord") {
df.[i,"dep.mod_peche"] <- df.[i,"dep_pdb"]
} else if (df.[i,"mod_peche"] == "peche embarquée") {
df.[i,"dep.mod_peche"] <- df.[i,"dep_pe"]
} else if (df.[i,"mod_peche"] == "chasse sous-marine") {
df.[i,"dep.mod_peche"] <- df.[i,"dep_csm"]
} else if (df.[i,"mod_peche"] == "peche à l'oursin") {
df.[i,"dep.mod_peche"] <- df.[i,"dep_po"]
}
}
df.$dep.mod_peche <- ifelse(df.$dep.mod_peche == 0, NA, df.$dep.mod_peche)
unique(df.$dep.mod_peche); length(na.omit(df.$dep.mod_peche)) ; table(df.$dep.mod_peche) ; table(df.$a, df.$dep.mod_peche) #no data for 2023
## [1] 2 1 3 4 5 NA
## [1] 258
##
## 1 2 3 4 5
## 94 59 29 25 51
##
## 1 2 3 4 5
## 2020 70 17 4 5 4
## 2021 10 17 12 12 23
## 2022 14 25 13 8 24
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
# 1= "< 100 euros"; 2="entre 100-500 euros"; 3= "entre 500-1000 euros"; 4= "entre 1000-2000 euros";5 ="supérieur à 2000"
df.$dep.mod_peche.chr <- as.character(df.$dep.mod_peche)
df.$dep.mod_peche.chr <- ifelse(is.na(df.$dep.mod_peche.chr), "NA", df.$dep.mod_peche.chr)
for (i in 1:nrow(df.)) {
if (df.[i,"dep.mod_peche.chr"] == "1") {
df.[i,"dep.mod_peche.chr"] <- "< 100 euros"
} else if (df.[i,"dep.mod_peche.chr"] == "2") {
df.[i,"dep.mod_peche.chr"] <- "entre 100-500 euros"
} else if (df.[i,"dep.mod_peche.chr"] == "3") {
df.[i,"dep.mod_peche.chr"] <- "entre 500-1000 euros"
} else if (df.[i,"dep.mod_peche.chr"] == "4") {
df.[i,"dep.mod_peche.chr"] <- "entre 1000-2000 euros"
} else if (df.[i,"dep.mod_peche.chr"] == "5") {
df.[i,"dep.mod_peche.chr"] <- "supérieur à 2000"
} else {
df.[i,"dep.mod_peche.chr"] <- NA
}
}
df.$dep.median.rd.chr <- as.character(df.$dep.median.rd)
df.$dep.median.rd.chr <- ifelse(is.na(df.$dep.median.rd.chr), "NA", df.$dep.median.rd.chr)
for (i in 1:nrow(df.)) {
if (df.[i,"dep.median.rd.chr"] == "1") {
df.[i,"dep.median.rd.chr"] <- "< 100 euros"
} else if (df.[i,"dep.median.rd.chr"] == "2") {
df.[i,"dep.median.rd.chr"] <- "entre 100-500 euros"
} else if (df.[i,"dep.median.rd.chr"] == "3") {
df.[i,"dep.median.rd.chr"] <- "entre 500-1000 euros"
} else if (df.[i,"dep.median.rd.chr"] == "4") {
df.[i,"dep.median.rd.chr"] <- "entre 1000-2000 euros"
} else if (df.[i,"dep.median.rd.chr"] == "5") {
df.[i,"dep.median.rd.chr"] <- "supérieur à 2000"
} else {
df.[i,"dep.median.rd.chr"] <- NA
}
}
rm(i)
df.$a <- as.factor(df.$a)
df.$mod_peche <- as.factor(df.$mod_peche)
df.$age_classe <- as.factor(df.$age_classe)
df.$cat_pro.gp <- as.factor(df.$cat_pro.gp)
df.$nb_sort_an <- as.numeric(df.$nb_sort_an)
df.$classe_avis_pnm <- as.factor(df.$classe_avis_pnm)
df.$sexe <- as.factor(df.$sexe)
df.$res_tour <- as.factor(df.$res_tour)
df.$espcib1 <- as.factor(df.$espcib1)
df.$espcib2 <- as.factor(df.$espcib2)
df.$espcib3 <- as.factor(df.$espcib3)
df.$poss_bat <- as.factor(df.$poss_bat)
df.$Temps_peche_estime.cat2h <- as.factor(df.$Temps_peche_estime.cat2h)
df.$Temps_peche_effectif.cat2h <- as.factor(df.$Temps_peche_effectif.cat2h)
df.$time.day.gp <- as.factor(df.$time.day.gp)
df.$zone.gp <- as.factor(df.$zone.gp)
df.$nb_sort_an_cat <- as.factor(df.$nb_sort_an_cat)
df.$dep.mod_peche.chr <- as.factor(df.$dep.mod_peche.chr)
df.$dep.median.rd.chr <- as.factor(df.$dep.median.rd.chr)
nrow(filter(df., a %in% c("2020", "2021", "2022")))
## [1] 261
nrow(filter(df., a %in% c("2023")))
## [1] 172
# reduce df. for multivariate spatial analysis ####
df.msa <- df.[, c("a", "mod_peche","age_classe","cat_pro.gp"
, "classe_avis_pnm"
, "sexe"
, "res_tour"
, "espcib1", "espcib2", "espcib3"
, "poss_bat"
, "Temps_peche_estime.cat2h"
, "Temps_peche_effectif.cat2h"
, "time.day.gp"
, "zone.gp"
, "nb_sort_an_cat"
, "dep.mod_peche.chr"
, "dep.median.rd.chr"
)]
length(na.omit((filter(df.msa, as.character(df.msa$a) != "NA"))[,"a"]))
## [1] 515
length(na.omit((filter(df.msa, as.character(df.msa$mod_peche) != "NA"))[,"mod_peche"]))
## [1] 517
length(na.omit((filter(df.msa, as.character(df.msa$age_classe) != "NA"))[,"age_classe"]))
## [1] 260
length(na.omit((filter(df.msa, as.character(df.msa$cat_pro.gp) != "NA"))[,"cat_pro.gp"]))
## [1] 260
length(na.omit((filter(df.msa, as.character(df.msa$nb_sort_an_cat) != "NA"))[,"nb_sort_an_cat"]))
## [1] 261
length(na.omit((filter(df.msa, as.character(df.msa$classe_avis_pnm) != "NA"))[,"classe_avis_pnm"]))
## [1] 260
length(na.omit((filter(df.msa, as.character(df.msa$sexe) != "NA"))[,"sexe"]))
## [1] 517
length(na.omit((filter(df.msa, as.character(df.msa$res_tour) != "NA"))[,"res_tour"]))
## [1] 517
length(na.omit((filter(df.msa, as.character(df.msa$espcib1) != "NA"))[,"espcib1"]))
## [1] 165
length(na.omit((filter(df.msa, as.character(df.msa$espcib2) != "NA"))[,"espcib2"]))
## [1] 76
length(na.omit((filter(df.msa, as.character(df.msa$espcib3) != "NA"))[,"espcib3"]))
## [1] 49
length(na.omit((filter(df.msa, as.character(df.msa$poss_bat) != "NA"))[,"poss_bat"]))
## [1] 261
length(na.omit((filter(df.msa, as.character(df.msa$Temps_peche_estime.cat2h) != "NA"))[,"Temps_peche_estime.cat2h"]))
## [1] 517
length(na.omit((filter(df.msa, as.character(df.msa$Temps_peche_effectif.cat2h) != "NA"))[,"Temps_peche_effectif.cat2h"]))
## [1] 472
length(na.omit((filter(df.msa, as.character(df.msa$time.day.gp) != "NA"))[,"time.day.gp"]))
## [1] 260
length(na.omit((filter(df.msa, as.character(df.msa$zone.gp) != "NA"))[,"zone.gp"]))
## [1] 516
length(na.omit((filter(df.msa, as.character(df.msa$nb_sort_an_cat) != "NA"))[,"nb_sort_an_cat"]))
## [1] 261
length(na.omit((filter(df.msa, as.character(df.msa$dep.median.rd.chr) != "NA"))[,"dep.median.rd.chr"]))
## [1] 260
length(na.omit((filter(df.msa, as.character(df.msa$dep.mod_peche.chr) != "NA"))[,"dep.mod_peche.chr"]))
## [1] 258
#There are variables with n ~ 517, when surveyed in 2023, and variables with n ~ 260, when only surveyed in 2020-2022, but not 2023. So we cannot do the full multivariate spatial analysis with all the variables for 2023 ; and for espece cible, even less data ...
# plot FAMD ####
#La MFA a été utilisée pour discriminer les modes de peche (bateau, du bord, chasse sous-marine, oursin) en fonction de 5 variables quantitatives et qualitatives (âge, profil, activité, nombre de sortie, avis sur le PNMCCA).
#I am not sure about the variables, groups of variables Michel used in his analysis ...
#obviously, except for "profil", one variable per group ... Special case : if each group has just one variable =) Factor Analysis of Mixed Data (FAMD)
#MFA: http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/116-mfa-multiple-factor-analysis-in-r-essentials/
#FAMD: http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/115-famd-factor-analysis-of-mixed-data-in-r-essentials/
# #2020-2023
# df.FAMD.red <- df.msa[, c("a",
# "mod_peche",
# "sexe",
# "res_tour",
# "Temps_peche_estime.cat2h",
# "zone.gp")
# ]
#
# #2020-2022
# df.FAMD <- df.msa[, c(
# #"a",
# "mod_peche",
# "sexe",
# "res_tour",
# "Temps_peche_estime.cat2h",
# "zone.gp",
# "age_classe",
# "cat_pro.gp",
# "nb_sort_an_cat",
# "classe_avis_pnm",
# "poss_bat",
# "time.day.gp",
# "nb_sort_an_cat",
# "dep.median.rd.chr",
# "dep.mod_peche.chr")
# ]
#write.csv2(na.omit(df.FAMD), "df.FAMD.csv") ##for ChatGPT
# Actually, because we now only have categorical variables, it is not an FAMD anymore but a Multiple correspondence analysis (MCA) (equivalent to ACP but for a df with categorical variables only)
#res.famd <- FAMD(na.omit(df.FAMD))
#print(res.famd)
#(eig.val <- get_eigenvalue(res.famd))
#fviz_screeplot(res.famd)
#(var <- get_famd_var(res.famd))
#var$coord # Coordinates of variables
# var$cos2 # Cos2: quality of representation on the factor map
# var$contrib # Contributions to the dimensions
# fviz_famd_var(res.famd, repel = TRUE) # Plot of variables
# fviz_contrib(res.famd, "var", axes = 1) # Contribution to the first dimension
# fviz_contrib(res.famd, "var", axes = 2 )# Contribution to the second dimension
# quanti.var <- get_famd_var(res.famd, "quanti.var")
# quanti.var
# quanti.var$cos2
# #fviz_famd_var(res.famd, "quanti.var", repel = TRUE, col.var = "black")
# quali.var <- get_famd_var(res.famd, "quali.var")
# quali.var
# fviz_famd_var(res.famd, "quali.var", repel = TRUE, col.var = "black", label = "none")
# ind <- get_famd_ind(res.famd)
# ind
# fviz_famd_ind(res.famd, col.ind = "cos2", repel = TRUE
# # ,label = "none"
# )
# fviz_mfa_ind(res.famd, habillage = "mod_peche", addEllipses = TRUE, ellipse.type = "confidence", label = "none", repel = TRUE # Avoid text overlapping
# )
#
# filter(df.FAMD, age_classe=="13-24", cat_pro=="etudiant")
# filter(df.FAMD, cat_pro=="etudiant")
# df.FAMD.red <- filter(df.FAMD, cat_pro!="etudiant")
#
# res.famd <- FAMD(df.FAMD.red, graph = T)
# print(res.famd)
# (eig.val <- get_eigenvalue(res.famd))
# fviz_screeplot(res.famd)
# (var <- get_famd_var(res.famd))
# var$coord # Coordinates of variables
# var$cos2 # Cos2: quality of representation on the factor map
# var$contrib # Contributions to the dimensions
# fviz_famd_var(res.famd, repel = TRUE) # Plot of variables
# fviz_contrib(res.famd, "var", axes = 1) # Contribution to the first dimension
# fviz_contrib(res.famd, "var", axes = 2 )# Contribution to the second dimension
#
# quanti.var <- get_famd_var(res.famd, "quanti.var")
# quanti.var
# quanti.var$cos2
# #fviz_famd_var(res.famd, "quanti.var", repel = TRUE, col.var = "black")
# quali.var <- get_famd_var(res.famd, "quali.var")
# quali.var
# fviz_famd_var(res.famd, "quali.var", repel = TRUE, col.var = "black", label = "none")
# ind <- get_famd_ind(res.famd)
# ind
# fviz_famd_ind(res.famd, col.ind = "cos2", repel = TRUE
# ,label = "none"
# )
# fviz_mfa_ind(res.famd, habillage = "mod_peche", addEllipses = TRUE, ellipse.type = "confidence", label = "none", repel = TRUE # Avoid text overlapping
# )
# plot MCA ####
#http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/114-mca-multiple-correspondence-analysis-in-r-essentials/
#In one variable there is a zero that must be removed in the df construction section above
#remove peche a l'oursin; also etudiant category here below before performing the analysis (but keep them for Kiviat or regression etc analysis )
#2020-2022
df.full <- na.omit(filter(df.msa[, c(
"a",
"mod_peche",
"sexe",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp",
"age_classe",
"cat_pro.gp",
"nb_sort_an_cat",
"classe_avis_pnm",
"poss_bat",
"time.day.gp",
#"dep.median.rd.chr",
"dep.mod_peche.chr")
], a %in% c("2020", "2021", "2022")))
df.full <- filter(df.full, cat_pro.gp != "etudiant")
df.full <- filter(df.full, age_classe != "13-24")
df.full <- filter(df.full, mod_peche != "peche à l'oursin")
#2020-2023
df.red <- na.omit(filter(df.msa[, c("a",
"mod_peche",
"sexe",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp")
], a %in% c("2020", "2021", "2022", "2023")))
df.red <- filter(df.red, mod_peche != "peche à l'oursin")
df.full <- droplevels(df.full)
summary(df.full)
## a mod_peche sexe res_tour
## 2020:98 chasse sous-marine: 13 femme: 6 occasionnel: 24
## 2021:70 peche du bord :113 homme:241 resident :191
## 2022:79 peche embarquée :121 secondaire : 17
## touriste : 15
##
##
## Temps_peche_estime.cat2h zone.gp age_classe
## <2h : 23 Agriates : 4 25-39 : 39
## >=2h:224 Est Cap :111 40-49 : 59
## nimp_ou : 78 50-59 :112
## Nord Cap : 5 60-69 : 21
## Ouest Cap : 23 70 et plus: 16
## Saint-Florent: 26
## cat_pro.gp nb_sort_an_cat classe_avis_pnm poss_bat
## activite :128 Q1 (<=10) :65 negatif: 2 non:129
## retraite : 96 Q2 (11-15):76 p_avis : 36 oui:118
## sans_emploi-en_arret: 23 Q3 (16-30):51 positif:209
## Q4 (>=31) :55
##
##
## time.day.gp dep.mod_peche.chr
## am :127 < 100 euros :88
## journee: 9 entre 100-500 euros :57
## nimp_q : 80 entre 1000-2000 euros:24
## nuit : 1 entre 500-1000 euros :28
## pm : 30 supérieur à 2000 :50
##
df.red <- droplevels(df.red)
summary(df.red)
## a mod_peche sexe res_tour
## 2020:102 chasse sous-marine: 37 femme: 14 occasionnel: 26
## 2021: 73 peche du bord :248 homme:416 resident :316
## 2022: 84 peche embarquée :145 secondaire : 25
## 2023:171 touriste : 63
##
##
## Temps_peche_estime.cat2h zone.gp
## <2h : 50 Agriates : 5
## >=2h:380 Est Cap :193
## nimp_ou :151
## Nord Cap : 6
## Ouest Cap : 28
## Saint-Florent: 47
# MCA: performed on one of the above df.
# df.full 2020-2022
unique(df.full$a)
## [1] 2020 2021 2022
## Levels: 2020 2021 2022
res.mca <- MCA(df.full, ncp = ncol(df.full), graph = TRUE)
## Warning: ggrepel: 33 unlabeled data points (too many overlaps). Consider
## increasing max.overlaps
#res.mca <- MCA(df.full[, 3:ncol(df.full)], ncp = ncol(df.full[, 3:ncol(df.full)]), graph = TRUE)
# Eigenvalues / Variances = The proportion of variances retained by the different dimensions (axes)
(eig.val <- get_eigenvalue(res.mca))
## eigenvalue variance.percent cumulative.variance.percent
## Dim.1 0.335420719 12.8249098 12.82491
## Dim.2 0.174834182 6.6848364 19.50975
## Dim.3 0.169892616 6.4958942 26.00564
## Dim.4 0.134410088 5.1392092 31.14485
## Dim.5 0.120103132 4.5921786 35.73703
## Dim.6 0.115177154 4.4038324 40.14086
## Dim.7 0.107720359 4.1187196 44.25958
## Dim.8 0.095712733 3.6596045 47.91918
## Dim.9 0.094522008 3.6140768 51.53326
## Dim.10 0.093722120 3.5834928 55.11675
## Dim.11 0.089150328 3.4086890 58.52544
## Dim.12 0.084464336 3.2295187 61.75496
## Dim.13 0.081319550 3.1092769 64.86424
## Dim.14 0.078509719 3.0018422 67.86608
## Dim.15 0.073771469 2.8206738 70.68675
## Dim.16 0.071430227 2.7311557 73.41791
## Dim.17 0.066725603 2.5512730 75.96918
## Dim.18 0.063049893 2.4107312 78.37991
## Dim.19 0.059969368 2.2929464 80.67286
## Dim.20 0.058999281 2.2558549 82.92872
## Dim.21 0.057185598 2.1865081 85.11522
## Dim.22 0.052068858 1.9908681 87.10609
## Dim.23 0.049428593 1.8899168 88.99601
## Dim.24 0.042654875 1.6309217 90.62693
## Dim.25 0.038458142 1.4704584 92.09739
## Dim.26 0.037856966 1.4474722 93.54486
## Dim.27 0.033433733 1.2783486 94.82321
## Dim.28 0.033070728 1.2644690 96.08768
## Dim.29 0.025542861 0.9766388 97.06432
## Dim.30 0.023539628 0.9000446 97.96436
## Dim.31 0.019011701 0.7269180 98.69128
## Dim.32 0.015014833 0.5740966 99.26538
## Dim.33 0.011398330 0.4358185 99.70120
## Dim.34 0.007814884 0.2988044 100.00000
fviz_screeplot(res.mca, addlabels = TRUE, ylim = c(0, eig.val[1,3]*1.1))
# Biplot of individuals and variable categories
fviz_mca_biplot(res.mca,
repel = TRUE, # Avoid text overlapping (slow if many point)
ggtheme = theme_minimal())
# Graph of variables
(var <- get_mca_var(res.mca))
## Multiple Correspondence Analysis Results for variables
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for categories"
## 2 "$cos2" "Cos2 for categories"
## 3 "$contrib" "contributions of categories"
# Coordinates
head(var$coord)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 2020 -1.0115717 0.09857426 -0.2461465 0.2124295 -0.03849555
## 2021 0.5758182 -0.78483228 -0.3123357 0.3932763 0.17437190
## 2022 0.7446424 0.57313901 0.5820995 -0.6119928 -0.10675277
## chasse sous-marine -0.6043628 -0.56725395 1.4281872 0.8111292 -0.43279705
## peche du bord -0.7506399 -0.13022136 0.1808663 -0.4187623 0.14178137
## peche embarquée 0.7659423 0.18255632 -0.3223498 0.3039294 -0.08590854
## Dim 6 Dim 7 Dim 8 Dim 9
## 2020 -0.03753824 0.007521064 -0.064429902 0.05408675
## 2021 0.25252806 0.087752224 0.080080679 0.02886669
## 2022 -0.17719261 -0.087085063 0.008968138 -0.09267304
## chasse sous-marine -0.38050418 1.848214082 -1.329270180 -0.77778763
## peche du bord 0.10725094 -0.138875950 0.247583662 -0.06038690
## peche embarquée -0.05927936 -0.068874386 -0.088400342 0.13995834
## Dim 10 Dim 11 Dim 12 Dim 13
## 2020 -0.14811960 -0.12139384 0.07978301 0.0842387
## 2021 0.18992428 0.02678713 0.16388384 -0.3501976
## 2022 0.01545596 0.12685440 -0.24418485 0.2058031
## chasse sous-marine -0.97541850 -1.39919799 -0.37985560 0.3436894
## peche du bord 0.22026751 0.25133575 0.02426777 -0.1512333
## peche embarquée -0.10090734 -0.08439146 0.01814764 0.1043091
# Cos2: quality on the factore map
head(var$cos2)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 2020 0.67302798 0.006390971 0.03984990 0.02968038 0.0009746774
## 2021 0.13112801 0.243600675 0.03858052 0.06116743 0.0120247976
## 2022 0.26074343 0.154467727 0.15933538 0.17612070 0.0053589059
## chasse sous-marine 0.02029191 0.017876502 0.11331770 0.03655170 0.0104062938
## peche du bord 0.47515677 0.014300068 0.02758601 0.14787975 0.0169516502
## peche embarquée 0.56338722 0.032004319 0.09978598 0.08870747 0.0070874088
## Dim 6 Dim 7 Dim 8 Dim 9
## 2020 0.0009268034 3.720475e-05 2.730328e-03 0.001924073
## 2021 0.0252199403 3.045377e-03 2.536181e-03 0.000329548
## 2022 0.0147641702 3.566196e-03 3.782007e-05 0.004038542
## chasse sous-marine 0.0080435240 1.897720e-01 9.816440e-02 0.033608533
## peche du bord 0.0097000929 1.626401e-02 5.169132e-02 0.003075099
## peche embarquée 0.0033745962 4.555440e-03 7.504517e-03 0.018811022
## Dim 10 Dim 11 Dim 12 Dim 13
## 2020 0.0144299507 0.0096924395 0.0041865917 0.004667273
## 2021 0.0142654593 0.0002837769 0.0106217734 0.048501054
## 2022 0.0001123336 0.0075670893 0.0280385307 0.019916885
## chasse sous-marine 0.0528578472 0.1087641678 0.0080161266 0.006562357
## peche du bord 0.0409142437 0.0532699386 0.0004966305 0.019287180
## peche embarquée 0.0097782320 0.0068393024 0.0003162680 0.010448633
# Contributions to the principal components
head(var$contrib)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5 Dim 6
## 2020 9.3108471 0.1696237 1.0884254 1.024669 0.03765759 0.03733939
## 2021 2.1549567 7.6804223 1.2517757 2.508542 0.55189493 1.20700945
## 2022 4.0671712 4.6225369 4.9068943 6.855632 0.23344833 0.67067432
## chasse sous-marine 0.4408681 0.7451295 4.8606997 1.981761 0.63141850 0.50892709
## peche du bord 5.9116884 0.3413314 0.6776084 4.591360 0.58900928 0.35145849
## peche embarquée 6.5909398 0.7183109 2.3047577 2.589754 0.23155992 0.11497031
## Dim 7 Dim 8 Dim 9 Dim 10 Dim 11
## 2020 0.001602679 0.132370436 0.09445711 0.714444845 0.50449413
## 2021 0.155839019 0.146064109 0.01921847 0.839028313 0.01754636
## 2022 0.173211346 0.002067386 0.22354277 0.006270997 0.44409398
## chasse sous-marine 12.838367539 7.474116374 2.59114771 4.110010379 8.89075098
## peche du bord 0.630078169 2.253784487 0.13576590 1.821784137 2.49358250
## peche embarquée 0.165944458 0.307668647 0.78092567 0.409400597 0.30103646
## Dim 12 Dim 13
## 2020 0.23000284 0.2663264
## 2021 0.69319691 3.2876772
## 2022 1.73680418 1.2814316
## chasse sous-marine 0.69161873 0.5880855
## peche du bord 0.02453717 0.9897791
## peche embarquée 0.01469306 0.5041906
# Correlation between variables and principal dimensions
fviz_mca_var(res.mca, choice = "mca.cor",
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
ggsave("Figs/MCA/variables_2020-2022.png", width = 7, height = 4, bg = "white")
# Coordinates of variable categories
fviz_mca_var(res.mca,
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
# Quality of representation of variable categories: the squared cosine (cos2) measures the degree of association between variable categories and a particular axis (quality on the factor map)
fviz_mca_var(res.mca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping
ggtheme = theme_minimal())
# Contribution of variable categories to the dimensions
# Contributions of rows to dimension 1
fviz_contrib(res.mca, choice = "var", axes = 1, top = 15)
# Contributions of rows to dimension 2
fviz_contrib(res.mca, choice = "var", axes = 2, top = 15)
# Total contribution to dimension 1 and 2
fviz_contrib(res.mca, choice = "var", axes = 1:2, top = 15)
# Color the most important (or, contributing) variable categories
fviz_mca_var(res.mca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # avoid text overlapping (slow)
ggtheme = theme_minimal()
)
# Graph of individuals
(ind <- get_mca_ind(res.mca))
## Multiple Correspondence Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"
# Plots: quality and contribution
# color individuals by their cos2 values
fviz_mca_ind(res.mca, col.ind = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping (slow if many points)
ggtheme = theme_minimal())
# Cos2 of individuals
fviz_cos2(res.mca, choice = "ind", axes = 1:2, top = 20)
# Contribution of individuals to the dimensions
fviz_contrib(res.mca, choice = "ind", axes = 1:2, top = 20)
# Color individuals by groups
fviz_mca_ind(res.mca,
label = "none", # hide individual labels
habillage = "mod_peche", # color by groups
#palette = c("#00AFBB", "#E7B800"),
addEllipses = TRUE, ellipse.type = "confidence",
ggtheme = theme_minimal())
# color individuals using multiple categorical variables
fviz_ellipses(res.mca, c("a", "mod_peche"),
geom = "point",
)
## Warning: `gather_()` was deprecated in tidyr 1.2.0.
## ℹ Please use `gather()` instead.
## ℹ The deprecated feature was likely used in the factoextra package.
## Please report the issue at <https://github.com/kassambara/factoextra/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
ggsave("Figs/MCA/factor.map_2020-2022.png", width = 10, height = 5)
# Dimension description: to identify the most correlated variables with a given dimension
res.desc <- dimdesc(res.mca, axes = c(1,2))
# Description of dimension 1
res.desc[[1]]
##
## Link between the variable and the categorical variable (1-way anova)
## =============================================
## R2 p.value
## a 0.6773106 1.179589e-60
## dep.mod_peche.chr 0.6680994 9.014491e-57
## poss_bat 0.6014861 7.421136e-51
## mod_peche 0.5643972 9.312428e-45
## zone.gp 0.5044372 6.659239e-35
## time.day.gp 0.4450028 6.285304e-30
## nb_sort_an_cat 0.4234219 7.179996e-29
## age_classe 0.1872689 3.003179e-10
## res_tour 0.1582001 4.146728e-09
## cat_pro.gp 0.1006037 2.410101e-06
##
## Link between variable and the categories of the categorical variables
## ================================================================
## Estimate p.value
## poss_bat=oui 0.4496130 7.421136e-51
## mod_peche=peche embarquée 0.5573186 5.520430e-46
## zone.gp=nimp_ou 0.3353256 5.186103e-27
## dep.mod_peche.chr=supérieur à 2000 0.4422827 3.163157e-19
## time.day.gp=nimp_q 0.3286835 3.040006e-18
## a=2022 0.3716320 8.343877e-18
## nb_sort_an_cat=Q4 (>=31) 0.3752181 7.134080e-11
## a=2021 0.2738565 4.562354e-09
## nb_sort_an_cat=Q3 (16-30) 0.3462465 9.426350e-09
## age_classe=60-69 0.4822374 3.822885e-08
## dep.mod_peche.chr=entre 1000-2000 euros 0.3127344 1.546148e-05
## time.day.gp=journee 0.6984869 1.786283e-05
## cat_pro.gp=activite 0.2651106 8.805196e-04
## dep.mod_peche.chr=entre 500-1000 euros 0.1695835 1.053547e-03
## age_classe=70 et plus 0.2802873 1.361075e-03
## res_tour=touriste 0.5022576 2.282416e-03
## res_tour=resident 0.1165549 6.183374e-03
## zone.gp=Nord Cap 0.3566333 3.361847e-02
## zone.gp=Agriates 0.3783812 4.874473e-02
## zone.gp=Saint-Florent -0.4105996 3.869060e-02
## age_classe=50-59 -0.2498379 3.784137e-02
## mod_peche=chasse sous-marine -0.2363007 2.516596e-02
## nb_sort_an_cat=Q1 (<=10) -0.2250003 6.283733e-03
## age_classe=40-49 -0.3789679 1.115096e-03
## cat_pro.gp=sans_emploi-en_arret -0.3833899 2.622232e-06
## time.day.gp=am -0.2839627 2.615476e-07
## res_tour=occasionnel -0.5637642 1.002662e-08
## time.day.gp=pm -0.7357326 3.251832e-11
## nb_sort_an_cat=Q2 (11-15) -0.4964644 1.846356e-17
## zone.gp=Est Cap -0.5695076 5.225564e-25
## mod_peche=peche du bord -0.3210179 3.717063e-36
## dep.mod_peche.chr=< 100 euros -0.7316429 8.326769e-42
## poss_bat=non -0.4496130 7.421136e-51
## a=2020 -0.6454885 2.087350e-61
# Description of dimension 2
res.desc[[2]]
##
## Link between the variable and the categorical variable (1-way anova)
## =============================================
## R2 p.value
## res_tour 0.37051987 2.882588e-24
## age_classe 0.35083112 8.575827e-22
## nb_sort_an_cat 0.30909316 2.160245e-19
## a 0.28348240 2.176093e-18
## time.day.gp 0.28260459 1.239576e-16
## cat_pro.gp 0.17959015 3.249117e-11
## zone.gp 0.19410703 4.624998e-10
## sexe 0.10705079 1.428212e-07
## classe_avis_pnm 0.08260609 2.702800e-05
## dep.mod_peche.chr 0.05838848 5.560173e-03
## mod_peche 0.04101966 6.036485e-03
##
## Link between variable and the categories of the categorical variables
## ================================================================
## Estimate p.value
## res_tour=touriste 0.55398319 1.045254e-18
## age_classe=60-69 0.46290216 6.828915e-13
## cat_pro.gp=retraite 0.24811719 3.636207e-12
## a=2022 0.25541385 1.502441e-10
## nb_sort_an_cat=Q1 (<=10) 0.28059914 1.756827e-10
## zone.gp=Nord Cap 0.96698740 1.077989e-09
## time.day.gp=am 0.02920505 5.855031e-09
## sexe=femme 0.44431495 1.428212e-07
## age_classe=70 et plus 0.35691728 6.769745e-07
## classe_avis_pnm=negatif 0.70959233 1.220565e-04
## time.day.gp=nuit 1.37992077 2.980777e-04
## zone.gp=Saint-Florent 0.09576652 4.201935e-03
## mod_peche=peche embarquée 0.14810060 4.800582e-03
## dep.mod_peche.chr=< 100 euros 0.11747337 5.461432e-03
## nb_sort_an_cat=Q3 (16-30) 0.12024294 2.931545e-02
## cat_pro.gp=sans_emploi-en_arret -0.13694427 4.986744e-02
## zone.gp=Agriates -0.54627819 4.265040e-02
## mod_peche=chasse sous-marine -0.16541890 3.572116e-02
## classe_avis_pnm=p_avis -0.26290006 2.185593e-02
## age_classe=40-49 -0.24477737 2.119362e-02
## dep.mod_peche.chr=entre 500-1000 euros -0.15644543 1.872252e-02
## time.day.gp=pm -0.28832026 1.657082e-02
## res_tour=occasionnel -0.10382495 1.287835e-02
## time.day.gp=nimp_q -0.21481473 1.081901e-02
## res_tour=secondaire -0.02734815 4.383317e-03
## classe_avis_pnm=positif -0.44669227 1.356393e-03
## age_classe=25-39 -0.41066930 5.294132e-06
## sexe=homme -0.44431495 1.428212e-07
## cat_pro.gp=activite -0.11117292 4.072280e-08
## time.day.gp=journee -0.90599083 2.742676e-09
## nb_sort_an_cat=Q4 (>=31) -0.36723720 1.550607e-15
## a=2021 -0.31239710 1.429846e-16
## res_tour=resident -0.42281009 1.913099e-18
# df.short 2020-2023
unique(df.red$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
res.mca <- MCA(df.red, ncp = ncol(df.red), graph = TRUE)
#res.mca <- MCA(df.red[, 3:ncol(df.red)], ncp = ncol(df.red[, 3:ncol(df.red)]), graph = TRUE)
# Eigenvalues / Variances = The proportion of variances retained by the different dimensions (axes)
(eig.val <- get_eigenvalue(res.mca))
## eigenvalue variance.percent cumulative.variance.percent
## Dim.1 0.32198375 12.879350 12.87935
## Dim.2 0.26768458 10.707383 23.58673
## Dim.3 0.21679999 8.672000 32.25873
## Dim.4 0.19341812 7.736725 39.99546
## Dim.5 0.18201108 7.280443 47.27590
## Dim.6 0.17206075 6.882430 54.15833
## Dim.7 0.16667803 6.667121 60.82545
## Dim.8 0.16247438 6.498975 67.32443
## Dim.9 0.15399520 6.159808 73.48424
## Dim.10 0.14634988 5.853995 79.33823
## Dim.11 0.13711975 5.484790 84.82302
## Dim.12 0.12795098 5.118039 89.94106
## Dim.13 0.10619903 4.247961 94.18902
## Dim.14 0.07808239 3.123296 97.31232
## Dim.15 0.06719209 2.687683 100.00000
fviz_screeplot(res.mca, addlabels = TRUE, ylim = c(0, eig.val[1,3]*1.1))
# Biplot of individuals and variable categories
fviz_mca_biplot(res.mca,
repel = TRUE, # Avoid text overlapping (slow if many point)
ggtheme = theme_minimal())
# Graph of variables
(var <- get_mca_var(res.mca))
## Multiple Correspondence Analysis Results for variables
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for categories"
## 2 "$cos2" "Cos2 for categories"
## 3 "$contrib" "contributions of categories"
# Coordinates
head(var$coord)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 2020 -0.9038502 -1.08158724 0.5251827 0.1189514 -0.13179656
## 2021 1.0088546 -0.74164783 -0.5797400 0.2398703 -0.18872318
## 2022 1.0424783 0.19428298 0.6300326 -0.1102970 0.63373740
## 2023 -0.4036365 0.86632994 -0.3752652 -0.1191733 -0.15212807
## chasse sous-marine -0.5790843 0.84404690 0.7217431 1.9269096 0.15204399
## peche du bord -0.5223164 0.08987206 -0.3148972 -0.2911672 0.01031209
## Dim 6
## 2020 0.08807654
## 2021 0.62418237
## 2022 -0.52601756
## 2023 -0.06060611
## chasse sous-marine 0.58659113
## peche du bord -0.02879844
# Cos2: quality on the factore map
head(var$cos2)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 2020 0.25405001 0.363788897 0.08577231 0.004400132 0.0054017499
## 2021 0.20811903 0.112473473 0.06872601 0.011765423 0.0072829134
## 2022 0.26383795 0.009163739 0.09636719 0.002953458 0.0975038707
## 2023 0.10756656 0.495522063 0.09297645 0.009376786 0.0152797081
## chasse sous-marine 0.03157133 0.067072166 0.04904271 0.349568148 0.0021764448
## peche du bord 0.37174719 0.011006004 0.13511949 0.115522122 0.0001449017
## Dim 6
## 2020 0.002412386
## 2021 0.079666849
## 2022 0.067174381
## 2023 0.002425097
## chasse sous-marine 0.032395162
## peche du bord 0.001130104
# Contributions to the principal components
head(var$contrib)
## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 2020 10.030888 17.2774730 5.029699 0.2892163 0.377303452
## 2021 8.943888 5.8140031 4.386421 0.8417030 0.553676162
## 2022 10.989039 0.4590983 5.961099 0.2047812 7.184233193
## 2023 3.353694 18.5831657 4.305204 0.4866726 0.842747137
## chasse sous-marine 1.493591 3.8167334 3.445784 27.5300845 0.182147275
## peche du bord 8.144519 0.2900401 4.396534 4.2132738 0.005616001
## Dim 6
## 2020 0.17824573
## 2021 6.40684692
## 2022 5.23574235
## 2023 0.14149054
## chasse sous-marine 2.86794748
## peche du bord 0.04633276
# Correlation between variables and principal dimensions
fviz_mca_var(res.mca, choice = "mca.cor",
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
ggsave("Figs/MCA/variables_2020-2023.png", width = 7, height = 4, bg = "white")
# Coordinates of variable categories
fviz_mca_var(res.mca,
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
# Quality of representation of variable categories: the squared cosine (cos2) measures the degree of association between variable categories and a particular axis (quality on the factor map)
fviz_mca_var(res.mca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping
ggtheme = theme_minimal())
# Contribution of variable categories to the dimensions
# Contributions of rows to dimension 1
fviz_contrib(res.mca, choice = "var", axes = 1, top = 15)
# Contributions of rows to dimension 2
fviz_contrib(res.mca, choice = "var", axes = 2, top = 15)
# Total contribution to dimension 1 and 2
fviz_contrib(res.mca, choice = "var", axes = 1:2, top = 15)
# Color the most important (or, contributing) variable categories
fviz_mca_var(res.mca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # avoid text overlapping (slow)
ggtheme = theme_minimal()
)
# Graph of individuals
(ind <- get_mca_ind(res.mca))
## Multiple Correspondence Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"
# Plots: quality and contribution
# color individuals by their cos2 values
fviz_mca_ind(res.mca, col.ind = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping (slow if many points)
ggtheme = theme_minimal())
# Cos2 of individuals
fviz_cos2(res.mca, choice = "ind", axes = 1:2, top = 20)
# Contribution of individuals to the dimensions
fviz_contrib(res.mca, choice = "ind", axes = 1:2, top = 20)
# Color individuals by groups
fviz_mca_ind(res.mca,
label = "none", # hide individual labels
habillage = "mod_peche", # color by groups
#palette = c("#00AFBB", "#E7B800"),
addEllipses = TRUE, ellipse.type = "confidence",
ggtheme = theme_minimal())
# color individuals using multiple categorical variables
fviz_ellipses(res.mca, c("a", "mod_peche"),
geom = "point")
ggsave("Figs/MCA/factor.map_2020-2023.png", width = 10, height = 5)
# Dimension description: to identify the most correlated variables with a given dimension
res.desc <- dimdesc(res.mca, axes = c(1,2))
# Description of dimension 1
res.desc[[1]]
##
## Link between the variable and the categorical variable (1-way anova)
## =============================================
## R2 p.value
## a 0.64366178 4.666496e-95
## mod_peche 0.55170173 4.069752e-75
## zone.gp 0.53851730 5.889304e-69
## res_tour 0.13793088 1.158544e-13
## Temps_peche_estime.cat2h 0.05901224 3.409007e-07
##
## Link between variable and the categories of the categorical variables
## ================================================================
## Estimate p.value
## mod_peche=peche embarquée 0.60216623 1.583987e-76
## zone.gp=nimp_ou 0.07635333 1.695352e-36
## a=2022 0.48601856 2.540008e-30
## a=2021 0.46693923 1.722929e-23
## res_tour=resident 0.34226686 1.247798e-10
## Temps_peche_estime.cat2h=>=2h 0.21500556 3.409007e-07
## zone.gp=Agriates 0.70136680 2.516450e-05
## zone.gp=Nord Cap 0.60197863 2.851180e-05
## zone.gp=Ouest Cap 0.03263364 1.797336e-04
## res_tour=touriste 0.09307550 2.743411e-02
## mod_peche=chasse sous-marine -0.31718919 2.128117e-04
## zone.gp=Saint-Florent -0.69122005 1.325412e-05
## Temps_peche_estime.cat2h=<2h -0.21500556 3.409007e-07
## res_tour=occasionnel -0.48001478 8.743909e-12
## a=2023 -0.33455925 3.057340e-12
## a=2020 -0.61839853 4.369850e-29
## zone.gp=Est Cap -0.72111235 1.013888e-40
## mod_peche=peche du bord -0.28497703 3.980343e-45
# Description of dimension 2
res.desc[[2]]
##
## Link between the variable and the categorical variable (1-way anova)
## =============================================
## R2 p.value
## a 0.6767132 4.735285e-104
## res_tour 0.5549917 1.558761e-74
## zone.gp 0.2007145 5.110941e-19
## mod_peche 0.1118963 9.931118e-12
## sexe 0.0556508 7.514404e-07
##
## Link between variable and the categories of the categorical variables
## ================================================================
## Estimate p.value
## a=2023 0.54686572 1.398417e-65
## res_tour=touriste 0.87132616 8.439161e-52
## zone.gp=nimp_ou 0.22272850 3.029369e-10
## mod_peche=chasse sous-marine 0.33928412 5.094610e-08
## sexe=femme 0.34385487 7.514404e-07
## zone.gp=Nord Cap 0.96862935 4.280563e-06
## a=2022 0.19916043 4.727528e-02
## zone.gp=Est Cap -0.04117422 4.851358e-02
## zone.gp=Agriates -0.45391227 4.230371e-02
## mod_peche=peche du bord -0.05091269 2.962093e-02
## zone.gp=Saint-Florent -0.20878840 1.757598e-03
## sexe=homme -0.34385487 7.514404e-07
## res_tour=resident -0.01229313 8.920363e-08
## zone.gp=Ouest Cap -0.48748296 7.776720e-08
## mod_peche=peche embarquée -0.28837144 3.001589e-08
## a=2021 -0.28507373 9.196268e-13
## res_tour=occasionnel -0.82970173 9.679304e-22
## a=2020 -0.46095241 5.949182e-44
# modelling ####
# Multinomial Logistic Regression Model
unique(survey$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
df.mod <- survey[, c(
#short model
"fiche_n"
, "a"
, "mod_peche"
, "res_tour"
, "z_1","z_2","z_3","z_4","z_6","z_7","z_8","z_9","z_54","z_55","z_56","z_57","z_58","z_59","z_60","z_61"
, "Temps_peche_estime"
# large model
, "age_moyen"
, "cat_pro"
, "nb_sort_an"
, "avis_pnm"
, "dep_pdb", "dep_pe", "dep_csm", "dep_po"
, "aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q"
, "poss_bat"
, "Temps_peche_effectif"
)]
#df.mod$a <- factor(df.mod$a, levels = c("2020", "2021", "2022", "2023", "2024"))
#df.mod %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> de.mod
# for model short
unique(df.mod$mod_peche)
## [1] "pdb" "csm" "pe" "po" "pdb, csm" NA
table(df.mod$mod_peche)
##
## csm pdb pdb, csm pe po
## 38 326 2 151 2
df.mod$mod_peche <- ifelse(df.mod$mod_peche == "csm", "chasse sous-marine", df.mod$mod_peche)
df.mod$mod_peche <- ifelse(df.mod$mod_peche == "pdb", "peche du bord", df.mod$mod_peche)
df.mod$mod_peche <- ifelse(df.mod$mod_peche == "pe", "peche embarquée", df.mod$mod_peche)
df.mod$mod_peche <- ifelse(df.mod$mod_peche == "po", "peche à l'oursin", df.mod$mod_peche)
table(df.mod$mod_peche)
##
## chasse sous-marine pdb, csm peche à l'oursin peche du bord
## 38 2 2 326
## peche embarquée
## 151
df.mod$mod_peche <- as.factor(df.mod$mod_peche)
nrow(df.mod) ; length(na.omit(df.mod$mod_peche))
## [1] 770
## [1] 519
unique(df.mod$mod_peche); length(na.omit(df.mod$mod_peche)) ; table(df.mod$mod_peche) ; table(df.mod$a, df.mod$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## [5] pdb, csm <NA>
## 5 Levels: chasse sous-marine pdb, csm peche à l'oursin ... peche embarquée
## [1] 519
##
## chasse sous-marine pdb, csm peche à l'oursin peche du bord
## 38 2 2 326
## peche embarquée
## 151
##
## chasse sous-marine pdb, csm peche à l'oursin peche du bord
## 2020 11 0 0 67
## 2021 2 0 1 21
## 2022 3 0 1 29
## 2023 21 2 0 131
## 2024 1 0 0 76
##
## peche embarquée
## 2020 24
## 2021 50
## 2022 52
## 2023 20
## 2024 5
table(df.mod$res_tour)
##
## occasionnel resident secondaire touriste
## 26 454 40 71
df.mod$res_tour <- ifelse(df.mod$res_tour %in% c("occasionnel", "secondaire", "touriste"), "non-resident", df.mod$res_tour)
table(df.mod$res_tour)
##
## non-resident resident
## 137 454
df.mod$res_tour <- as.factor(df.mod$res_tour)
df.spatial <- df.mod[, c("fiche_n","z_1","z_2","z_3","z_4","z_6","z_7","z_8","z_9","z_54","z_55","z_56","z_57","z_58","z_59","z_60","z_61")]
summary(df.spatial[,-1])
## z_1 z_2 z_3 z_4
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.1786 Mean :0.1935 Mean :0.146 Mean :0.1749
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## NA's :182 NA's :181 NA's :181 NA's :181
## z_6 z_7 z_8 z_9
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2139 Mean :0.3345 Mean :0.2326 Mean :0.3192
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :9.0000
## NA's :181 NA's :181 NA's :181 NA's :181
## z_54 z_55 z_56 z_57
## Min. :0.00000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.00000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.05433 Mean :0.0798 Mean :0.107 Mean :0.1188
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.0000 Max. :1.000 Max. :1.0000
## NA's :181 NA's :181 NA's :181 NA's :181
## z_58 z_59 z_60 z_61
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1749 Mean :0.3939 Mean :0.1902 Mean :0.1783
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :181 NA's :181 NA's :181 NA's :181
table(df.spatial$z_9)
##
## 0 1 9
## 409 179 1
df.spatial$z_9 <- ifelse(df.spatial$z_9 == 9, 1, df.spatial$z_9)
replace_values <- function(column_name, data) {
if (column_name %in% c("z_54", "z_55", "z_56", "z_57", "z_58", "z_59")) {
data[data == 1] <- "Agriates_St-Florent"
} else if (column_name %in% c("z_60", "z_61", "z_1", "z_2", "z_3")) {
data[data == 1] <- "Ouest-Nord Cap"
} else if (column_name %in% c("z_6", "z_7", "z_8", "z_9", "z_4")) {
data[data == 1] <- "Est-Nord Cap"
}
return(data)
}
cols_to_replace <- c("z_54", "z_55", "z_56", "z_57", "z_58", "z_59", "z_60", "z_61", "z_1", "z_2", "z_3", "z_4", "z_6", "z_7", "z_8", "z_9")
df.spatial[cols_to_replace] <- lapply(cols_to_replace, function(col) replace_values(col, df.spatial[[col]]))
concatenate_unique <- function(row) {
values <- as.character(row)
values <- values[values != "0"]
unique_values <- unique(values)
paste(unique_values, collapse = ", ")
}
df.spatial <- df.spatial %>%
rowwise() %>%
mutate(concatenated_values = concatenate_unique(c_across(2:17)))
df.spatial <- data.frame(df.spatial)
names(df.spatial)[names(df.spatial) == "concatenated_values"] <- "zone"
df.mod <- bind_cols(df.mod, df.spatial[,c("fiche_n", "zone")])
## New names:
## • `fiche_n` -> `fiche_n...1`
## • `fiche_n` -> `fiche_n...40`
df.mod <- subset(df.mod, select = -c(fiche_n...40))
names(df.mod)[names(df.mod) == "fiche_n...1"] <- "fiche_n"
rm(df.spatial)
unique(df.mod$zone); length(na.omit(df.mod$zone)) ; table(df.mod$zone) ; table(df.mod$a, df.mod$zone)
## [1] "Est-Nord Cap"
## [2] "Agriates_St-Florent"
## [3] "Ouest-Nord Cap"
## [4] "Ouest-Nord Cap, Est-Nord Cap, Agriates_St-Florent"
## [5] "Ouest-Nord Cap, Est-Nord Cap"
## [6] "Ouest-Nord Cap, Agriates_St-Florent"
## [7] "Agriates_St-Florent, Ouest-Nord Cap"
## [8] "Est-Nord Cap, Agriates_St-Florent"
## [9] "NA"
## [10] "NA, Est-Nord Cap"
## [11] "Est-Nord Cap, Agriates_St-Florent, Ouest-Nord Cap"
## [12] "Est-Nord Cap, Ouest-Nord Cap"
## [1] 770
##
## Agriates_St-Florent
## 112
## Agriates_St-Florent, Ouest-Nord Cap
## 36
## Est-Nord Cap
## 245
## Est-Nord Cap, Agriates_St-Florent
## 22
## Est-Nord Cap, Agriates_St-Florent, Ouest-Nord Cap
## 2
## Est-Nord Cap, Ouest-Nord Cap
## 1
## NA
## 181
## NA, Est-Nord Cap
## 1
## Ouest-Nord Cap
## 45
## Ouest-Nord Cap, Agriates_St-Florent
## 31
## Ouest-Nord Cap, Est-Nord Cap
## 45
## Ouest-Nord Cap, Est-Nord Cap, Agriates_St-Florent
## 49
##
## Agriates_St-Florent Agriates_St-Florent, Ouest-Nord Cap Est-Nord Cap
## 2020 20 0 73
## 2021 9 11 25
## 2022 13 12 21
## 2023 21 5 94
## 2024 45 8 19
##
## Est-Nord Cap, Agriates_St-Florent
## 2020 0
## 2021 2
## 2022 3
## 2023 11
## 2024 3
##
## Est-Nord Cap, Agriates_St-Florent, Ouest-Nord Cap
## 2020 0
## 2021 0
## 2022 0
## 2023 1
## 2024 0
##
## Est-Nord Cap, Ouest-Nord Cap NA NA, Est-Nord Cap Ouest-Nord Cap
## 2020 0 0 0 7
## 2021 0 0 0 10
## 2022 0 0 0 10
## 2023 0 1 1 3
## 2024 1 0 0 1
##
## Ouest-Nord Cap, Agriates_St-Florent Ouest-Nord Cap, Est-Nord Cap
## 2020 0 1
## 2021 7 4
## 2022 14 9
## 2023 4 12
## 2024 3 0
##
## Ouest-Nord Cap, Est-Nord Cap, Agriates_St-Florent
## 2020 1
## 2021 6
## 2022 3
## 2023 21
## 2024 2
df.mod$zone.gp <- df.mod$zone
df.mod$zone.gp <- ifelse(df.mod$zone.gp %notin% c("0", "NA",
"Est-Nord Cap", "Ouest-Nord Cap", "Agriates_St-Florent")
& !is.na(df.mod$zone.gp), "nimp_ou", df.mod$zone.gp)
unique(df.mod$zone.gp); length(na.omit(df.mod$zone.gp)) ; table(df.mod$zone.gp) ; table(df.mod$a, df.mod$zone.gp)
## [1] "Est-Nord Cap" "Agriates_St-Florent" "Ouest-Nord Cap"
## [4] "nimp_ou" "NA"
## [1] 770
##
## Agriates_St-Florent Est-Nord Cap NA nimp_ou
## 112 245 181 187
## Ouest-Nord Cap
## 45
##
## Agriates_St-Florent Est-Nord Cap NA nimp_ou Ouest-Nord Cap
## 2020 20 73 0 2 7
## 2021 9 25 0 30 10
## 2022 13 21 0 41 10
## 2023 21 94 1 55 3
## 2024 45 19 0 17 1
df.mod$zone.gp <- ifelse(df.mod$zone.gp == "NA", NA, df.mod$zone.gp)
unique(df.mod$zone.gp); length(na.omit(df.mod$zone.gp)) ; table(df.mod$zone.gp) ; table(df.mod$a, df.mod$zone.gp)
## [1] "Est-Nord Cap" "Agriates_St-Florent" "Ouest-Nord Cap"
## [4] "nimp_ou" NA
## [1] 589
##
## Agriates_St-Florent Est-Nord Cap nimp_ou Ouest-Nord Cap
## 112 245 187 45
##
## Agriates_St-Florent Est-Nord Cap nimp_ou Ouest-Nord Cap
## 2020 20 73 2 7
## 2021 9 25 30 10
## 2022 13 21 41 10
## 2023 21 94 55 3
## 2024 45 19 17 1
df.mod$zone.gp <- as.factor(df.mod$zone.gp)
df.mod %>%
mutate(Temps_peche_estime.30min = if_else(Temps_peche_estime < parse_hms("00:30:00"), NA, as_hms(Temps_peche_estime))) -> df.mod
df.mod$Temps_peche_estime.cat2h <- NA
for (i in 1:length(df.mod$Temps_peche_estime.30min)) {
#i=1
if (as.numeric(df.mod[i, "Temps_peche_estime.30min"]) < as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- "<2h"
} else if (as.numeric(df.mod[i, "Temps_peche_estime.30min"]) >= as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- ">=2h"
} else if (is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- NA
}
rm(i)
}
unique(df.mod$Temps_peche_estime.cat2h); length(na.omit(df.mod$Temps_peche_estime.cat2h)) ; table(df.mod$Temps_peche_estime.cat2h) ; table(df.mod$a, df.mod$Temps_peche_estime.cat2h)
## [1] ">=2h" "<2h" NA
## [1] 519
##
## <2h >=2h
## 60 459
##
## <2h >=2h
## 2020 11 91
## 2021 7 67
## 2022 10 75
## 2023 24 150
## 2024 7 75
df.mod$Temps_peche_estime.cat2h <- as.factor(df.mod$Temps_peche_estime.cat2h)
nrow(na.omit((filter(df.mod, as.character(df.mod$a) != "NA"))[,"a"]))
## [1] 517
nrow(na.omit((filter(df.mod, as.character(df.mod$mod_peche) != "NA"))[,"mod_peche"]))
## [1] 519
nrow(na.omit((filter(df.mod, as.character(df.mod$res_tour) != "NA"))[,"res_tour"]))
## [1] 591
nrow(na.omit((filter(df.mod, as.character(df.mod$Temps_peche_estime.cat2h) != "NA"))[,"Temps_peche_estime.cat2h"]))
## [1] 519
nrow(na.omit((filter(df.mod, as.character(df.mod$zone.gp) != "NA"))[,"zone.gp"]))
## [1] 589
# for model large
unique(df.mod$poss_bat); length(na.omit(df.mod$poss_bat)) ; table(df.mod$poss_bat) ; table(df.mod$a, df.mod$poss_bat)
## [1] "non" "oui" "NA" NA
## [1] 509
##
## NA non oui
## 248 138 123
##
## NA non oui
## 2020 0 82 20
## 2021 0 25 49
## 2022 0 31 54
## 2023 174 0 0
## 2024 0 0 0
df.mod$poss_bat <- ifelse(df.mod$poss_bat == "NA", NA, df.mod$poss_bat)
unique(df.mod$poss_bat); length(na.omit(df.mod$poss_bat)) ; table(df.mod$poss_bat) ; table(df.mod$a, df.mod$poss_bat)
## [1] "non" "oui" NA
## [1] 261
##
## non oui
## 138 123
##
## non oui
## 2020 82 20
## 2021 25 49
## 2022 31 54
## 2023 0 0
## 2024 0 0
df.mod %>%
mutate(Temps_peche_effectif.30min = if_else(Temps_peche_effectif < parse_hms("00:30:00"), NA, as_hms(Temps_peche_effectif))) -> df.mod
df.mod$Temps_peche_effectif.cat2h <- NA
for (i in 1:length(df.mod$Temps_peche_effectif.30min)) {
#i=1
if (as.numeric(df.mod[i, "Temps_peche_effectif.30min"]) < as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_effectif.30min"])) {
df.mod[i, "Temps_peche_effectif.cat2h"] <- "<2h"
} else if (as.numeric(df.mod[i, "Temps_peche_effectif.30min"]) >= as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_effectif.30min"])) {
df.mod[i, "Temps_peche_effectif.cat2h"] <- ">=2h"
} else if (is.na(df.mod[i, "Temps_peche_effectif.30min"])) {
df.mod[i, "Temps_peche_effectif.cat2h"] <- NA
}
rm(i)
}
df.mod %>%
mutate(Temps_peche_estime.30min = if_else(Temps_peche_estime < parse_hms("00:30:00"), NA, as_hms(Temps_peche_estime))) -> df.mod
df.mod$Temps_peche_estime.cat2h <- NA
for (i in 1:length(df.mod$Temps_peche_estime.30min)) {
#i=1
if (as.numeric(df.mod[i, "Temps_peche_estime.30min"]) < as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- "<2h"
} else if (as.numeric(df.mod[i, "Temps_peche_estime.30min"]) >= as.numeric(as.hms("02:00:00")) & !is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- ">=2h"
} else if (is.na(df.mod[i, "Temps_peche_estime.30min"])) {
df.mod[i, "Temps_peche_estime.cat2h"] <- NA
}
rm(i)
}
unique(df.mod$Temps_peche_effectif.cat2h); length(na.omit(df.mod$Temps_peche_effectif.cat2h)) ; table(df.mod$Temps_peche_effectif.cat2h) ; table(df.mod$a, df.mod$Temps_peche_effectif.cat2h)
## [1] "<2h" ">=2h" NA
## [1] 474
##
## <2h >=2h
## 233 241
##
## <2h >=2h
## 2020 57 29
## 2021 25 41
## 2022 27 51
## 2023 81 83
## 2024 41 37
unique(df.mod$Temps_peche_estime.cat2h); length(na.omit(df.mod$Temps_peche_estime.cat2h)) ; table(df.mod$Temps_peche_estime.cat2h) ; table(df.mod$a, df.mod$Temps_peche_estime.cat2h)
## [1] ">=2h" "<2h" NA
## [1] 519
##
## <2h >=2h
## 60 459
##
## <2h >=2h
## 2020 11 91
## 2021 7 67
## 2022 10 75
## 2023 24 150
## 2024 7 75
df.time <- survey[, c("fiche_n","aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q")]
summary(df.time[,-1])
## aube matin soir crepuscule
## Min. :0.0000 Min. :0.000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :1.000 Median :0.000 Median :0.0000
## Mean :0.1801 Mean :0.705 Mean :0.069 Mean :0.0805
## 3rd Qu.:0.0000 3rd Qu.:1.000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.000 Max. :1.000 Max. :1.0000
## NA's :509 NA's :509 NA's :509 NA's :509
## nuit apm journee nimp_q
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.0421 Mean :0.0996 Mean :0.0383 Mean :0.0843
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :509 NA's :509 NA's :509 NA's :509
replace_values <- function(column_name, data) {
if (column_name == "aube") {
data[data == 1] <- "aube"
} else if (column_name == "matin") {
data[data == 1] <- "matin"
} else if (column_name == "soir") {
data[data == 1] <- "soir"
} else if (column_name == "crepuscule") {
data[data == 1] <- "crepuscule"
} else if (column_name == "nuit") {
data[data == 1] <- "nuit"
} else if (column_name == "apm") {
data[data == 1] <- "apm"
} else if (column_name == "journee") {
data[data == 1] <- "journee"
} else if (column_name == "nimp_q") {
data[data == 1] <- "nimp_q"
}
return(data)
}
cols_to_replace <- c("aube", "matin", "soir", "crepuscule", "nuit", "apm", "journee", "nimp_q")
df.time[cols_to_replace] <- lapply(cols_to_replace, function(col) replace_values(col, df.time[[col]]))
concatenate_unique <- function(row) {
values <- as.character(row)
values <- values[values != "0"]
unique_values <- unique(values)
paste(unique_values, collapse = ", ")
}
df.time <- df.time %>%
rowwise() %>%
mutate(concatenated_values = concatenate_unique(c_across(2:9)))
df.time <- data.frame(df.time)
for (i in 1:nrow(df.time)) {
df.time[i,"concatenated_values"] <- ifelse(
df.time[i,"aube"]=="0"
& df.time[i,"matin"]=="0"
& df.time[i,"soir"]=="0"
& df.time[i,"crepuscule"]=="0"
& df.time[i,"nuit"]=="0"
& df.time[i,"apm"]=="0"
& df.time[i,"journee"]=="0"
& df.time[i,"nimp_q"]=="0"
& df.time[i,"concatenated_values"]==""
, "0", df.time[i,"concatenated_values"])
}
df.time[,"concatenated_values"] <- ifelse(df.time[,"concatenated_values"] == "NA", NA, df.time[,"concatenated_values"] )
names(df.time)[names(df.time) == "concatenated_values"] <- "time.day"
table(df.time[,2:10])
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 1 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = 0
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 3 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = apm
##
## matin
## aube 0 matin
## 0 0 0
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##
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##
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##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = aube, matin, crepuscule, apm
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = aube, matin, nuit
##
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##
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##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = aube, matin, nuit
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##
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##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, nuit
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##
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##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = aube, matin, nuit
##
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##
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##
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##
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##
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##
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##
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##
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##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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##
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##
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##
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##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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##
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## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
## matin
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##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = matin, soir, crepuscule, nuit
##
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##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = nuit
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 17 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = 0, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = 0, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = 0, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = 0, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = 0, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = 0, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
##
## , , soir = soir, crepuscule = crepuscule, nuit = nuit, apm = apm, journee = journee, nimp_q = nimp_q, time.day = soir
##
## matin
## aube 0 matin
## 0 0 0
## aube 0 0
df.mod <- bind_cols(df.mod, df.time[,c("fiche_n", "time.day")])
## New names:
## • `fiche_n` -> `fiche_n...1`
## • `fiche_n` -> `fiche_n...46`
df.mod <- subset(df.mod, select = -c(fiche_n...46))
names(df.mod)[names(df.mod) == "fiche_n...1"] <- "fiche_n"
rm(df.time,i)
unique(df.mod$time.day); length(na.omit(df.mod$time.day)) ; table(df.mod$time.day) ; table(df.mod$a, df.mod$time.day)
## [1] "matin" "soir"
## [3] "crepuscule" "matin, nuit"
## [5] "aube" "matin, journee"
## [7] "0" "matin, crepuscule"
## [9] "matin, crepuscule, apm" "matin, apm"
## [11] "journee" "aube, matin"
## [13] "aube, matin, apm" "matin, crepuscule, nuit"
## [15] "crepuscule, apm" "apm"
## [17] "nimp_q" "aube, matin, crepuscule"
## [19] "aube, matin, nuit" "crepuscule, nuit, apm"
## [21] "nuit" "aube, matin, crepuscule, apm"
## [23] "aube, crepuscule" "aube, nuit"
## [25] "matin, soir, crepuscule, nuit" NA
## [1] 261
##
## 0 apm
## 1 3
## aube aube, crepuscule
## 9 1
## aube, matin aube, matin, apm
## 27 5
## aube, matin, crepuscule aube, matin, crepuscule, apm
## 1 1
## aube, matin, nuit aube, nuit
## 2 1
## crepuscule crepuscule, apm
## 11 1
## crepuscule, nuit, apm journee
## 1 9
## matin matin, apm
## 125 13
## matin, crepuscule matin, crepuscule, apm
## 1 2
## matin, crepuscule, nuit matin, journee
## 1 1
## matin, nuit matin, soir, crepuscule, nuit
## 4 1
## nimp_q nuit
## 22 1
## soir
## 17
##
## 0 apm aube aube, crepuscule aube, matin aube, matin, apm
## 2020 0 0 0 0 0 0
## 2021 1 1 4 0 10 1
## 2022 0 2 5 1 17 4
## 2023 0 0 0 0 0 0
## 2024 0 0 0 0 0 0
##
## aube, matin, crepuscule aube, matin, crepuscule, apm aube, matin, nuit
## 2020 0 0 0
## 2021 0 0 0
## 2022 1 1 2
## 2023 0 0 0
## 2024 0 0 0
##
## aube, nuit crepuscule crepuscule, apm crepuscule, nuit, apm journee
## 2020 0 7 0 0 0
## 2021 0 2 1 0 9
## 2022 1 2 0 1 0
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
##
## matin matin, apm matin, crepuscule matin, crepuscule, apm
## 2020 78 0 0 0
## 2021 24 12 1 1
## 2022 23 1 0 1
## 2023 0 0 0 0
## 2024 0 0 0 0
##
## matin, crepuscule, nuit matin, journee matin, nuit
## 2020 0 0 0
## 2021 1 1 4
## 2022 0 0 0
## 2023 0 0 0
## 2024 0 0 0
##
## matin, soir, crepuscule, nuit nimp_q nuit soir
## 2020 0 0 0 17
## 2021 0 1 0 0
## 2022 1 21 1 0
## 2023 0 0 0 0
## 2024 0 0 0 0
df.mod$time.day.gp <- df.mod$time.day
df.mod$time.day.gp <- ifelse(df.mod$time.day.gp %in% c("aube", "matin"), "am", df.mod$time.day.gp)
df.mod$time.day.gp <- ifelse(df.mod$time.day.gp %in% c("apm", "crepuscule", "soir"), "pm", df.mod$time.day.gp)
df.mod$time.day.gp <- ifelse(df.mod$time.day.gp %notin% c("0", "NA",
"am", "pm", "nimp_q")
& !is.na(df.mod$time.day.gp), "nimp_q", df.mod$time.day.gp)
unique(df.mod$time.day.gp); length(na.omit(df.mod$time.day.gp)) ; table(df.mod$time.day.gp) ; table(df.mod$a, df.mod$time.day.gp)
## [1] "am" "pm" "nimp_q" "0" NA
## [1] 261
##
## 0 am nimp_q pm
## 1 134 95 31
##
## 0 am nimp_q pm
## 2020 0 78 0 24
## 2021 1 28 42 3
## 2022 0 28 53 4
## 2023 0 0 0 0
## 2024 0 0 0 0
# remove the variable level "0" that makes no sense
df.mod$time.day.gp <- ifelse(df.mod$time.day.gp == "0", NA, df.mod$time.day.gp)
unique(df.mod$time.day.gp); length(na.omit(df.mod$time.day.gp)) ; table(df.mod$time.day.gp) ; table(df.mod$a, df.mod$time.day.gp)
## [1] "am" "pm" "nimp_q" NA
## [1] 260
##
## am nimp_q pm
## 134 95 31
##
## am nimp_q pm
## 2020 78 0 24
## 2021 28 42 3
## 2022 28 53 4
## 2023 0 0 0
## 2024 0 0 0
df.mod <- add_column(df.mod, age_classe = NA, .after = "age_moyen")
df.mod$age_classe <- as.character(df.mod$age_classe)
df.mod <- data.frame(df.mod)
df.mod$age_classe <- ifelse(df.mod$age_moyen >= 60, "60 et plus", df.mod$age_classe)
df.mod$age_classe <- ifelse(df.mod$age_moyen >= 40 & df.mod$age_moyen < 60, "40-59", df.mod$age_classe)
df.mod$age_classe <- ifelse(df.mod$age_moyen < 40, "13-40", df.mod$age_classe)
unique(df.mod$age_classe)
## [1] "40-59" "13-40" "60 et plus" NA
nrow(df.mod) ; length(na.omit(df.mod$age_classe))
## [1] 770
## [1] 331
unique(df.mod$age_classe); length(na.omit(df.mod$age_classe)) ; table(df.mod$age_classe) ; table(df.mod$a, df.mod$age_classe)
## [1] "40-59" "13-40" "60 et plus" NA
## [1] 331
##
## 13-40 40-59 60 et plus
## 70 200 61
##
## 13-40 40-59 60 et plus
## 2020 15 87 0
## 2021 16 56 2
## 2022 14 34 36
## 2023 0 0 0
## 2024 0 0 0
unique(df.mod$cat_pro)
## [1] "activite" "retraite" "sans_emploi" "etudiant" "NA"
## [6] "en_arret" NA
df.mod$cat_pro <- ifelse(df.mod$cat_pro == "NA", NA, df.mod$cat_pro)
table(df.mod$cat_pro)
##
## activite en_arret etudiant retraite sans_emploi
## 175 3 11 118 25
nrow(df.mod) ; length(na.omit(df.mod$cat_pro))
## [1] 770
## [1] 332
table(df.mod[, c("a", "cat_pro")])
## cat_pro
## a activite en_arret etudiant retraite sans_emploi
## 2020 40 0 1 45 16
## 2021 47 1 0 23 2
## 2022 47 2 3 30 3
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
df.mod$cat_pro.gp <- df.mod$cat_pro
df.mod$cat_pro.gp <- ifelse(df.mod$cat_pro.gp %in% c("sans_emploi", "en_arret", "etudiant"), "sans_emploi-en_arret-etudiant", df.mod$cat_pro.gp)
table(df.mod$cat_pro.gp)
##
## activite retraite
## 175 118
## sans_emploi-en_arret-etudiant
## 39
unique(df.mod$cat_pro.gp); length(na.omit(df.mod$cat_pro.gp)) ; table(df.mod$cat_pro.gp) ; table(df.mod$a, df.mod$cat_pro.gp)
## [1] "activite" "retraite"
## [3] "sans_emploi-en_arret-etudiant" NA
## [1] 332
##
## activite retraite
## 175 118
## sans_emploi-en_arret-etudiant
## 39
##
## activite retraite sans_emploi-en_arret-etudiant
## 2020 40 45 17
## 2021 47 23 3
## 2022 47 30 8
## 2023 0 0 0
## 2024 0 0 0
unique(df.mod$avis_pnm)
## [1] "p_avis" "t_positif" "positif" "nsp" "_" "negatif"
## [7] "t_negatif" "NA" NA
df.mod <- add_column(df.mod, classe_avis_pnm = df.mod$avis_pnm, .after = "avis_pnm")
unique(df.mod$classe_avis_pnm)
## [1] "p_avis" "t_positif" "positif" "nsp" "_" "negatif"
## [7] "t_negatif" "NA" NA
df.mod$classe_avis_pnm <- ifelse(df.mod$classe_avis_pnm == "NA", NA, df.mod$classe_avis_pnm)
df.mod$classe_avis_pnm <- ifelse(df.mod$classe_avis_pnm == "_", NA, df.mod$classe_avis_pnm)
df.mod$classe_avis_pnm <- ifelse(df.mod$classe_avis_pnm == "t_positif", "positif", df.mod$classe_avis_pnm)
df.mod$classe_avis_pnm <- ifelse(df.mod$classe_avis_pnm == "t_negatif", "negatif", df.mod$classe_avis_pnm)
df.mod$classe_avis_pnm <- ifelse(df.mod$classe_avis_pnm == "nsp", "p_avis", df.mod$classe_avis_pnm)
table(df.mod$classe_avis_pnm)
##
## negatif p_avis positif
## 6 57 269
unique(df.mod$classe_avis_pnm); length(na.omit(df.mod$classe_avis_pnm)) ; table(df.mod$classe_avis_pnm) ; table(df.mod$a, df.mod$classe_avis_pnm)
## [1] "p_avis" "positif" NA "negatif"
## [1] 332
##
## negatif p_avis positif
## 6 57 269
##
## negatif p_avis positif
## 2020 0 16 86
## 2021 0 6 67
## 2022 2 18 65
## 2023 0 0 0
## 2024 0 0 0
unique(df.mod$nb_sort_an)
## [1] "5" "30" "15" "40" "0" "10"
## [7] "1" "50" "64" "48" "80" "20"
## [13] "illimite" "150" "24" "130" "52" "100"
## [19] "25" "4" "60" "12" "2" "22"
## [25] "NA" NA "35" "200" "6" "7"
## [31] "250" "8"
df.mod$nb_sort_an <- ifelse(df.mod$nb_sort_an == "NA", NA, df.mod$nb_sort_an)
df.mod$nb_sort_an <- ifelse(df.mod$nb_sort_an == "illimite", 999, df.mod$nb_sort_an)
table(df.mod$nb_sort_an) #or considering that variable as categorial, cfr idem classe_age?
##
## 0 1 10 100 12 130 15 150 2 20 200 22 24 25 250 30 35 4 40 48
## 3 8 19 8 4 1 82 3 5 18 1 1 2 4 1 52 1 3 31 1
## 5 50 52 6 60 64 7 8 80 999
## 46 14 1 2 5 1 1 1 2 12
nrow(df.mod) ; length(na.omit(df.mod$nb_sort_an))
## [1] 770
## [1] 333
unique(df.mod$nb_sort_an); length(na.omit(df.mod$nb_sort_an)) ; table(df.mod$nb_sort_an) ; table(df.mod$a, df.mod$nb_sort_an) #no data for 2023
## [1] "5" "30" "15" "40" "0" "10" "1" "50" "64" "48" "80" "20"
## [13] "999" "150" "24" "130" "52" "100" "25" "4" "60" "12" "2" "22"
## [25] NA "35" "200" "6" "7" "250" "8"
## [1] 333
##
## 0 1 10 100 12 130 15 150 2 20 200 22 24 25 250 30 35 4 40 48
## 3 8 19 8 4 1 82 3 5 18 1 1 2 4 1 52 1 3 31 1
## 5 50 52 6 60 64 7 8 80 999
## 46 14 1 2 5 1 1 1 2 12
##
## 0 1 10 100 12 130 15 150 2 20 200 22 24 25 250 30 35 4 40 48 5 50
## 2020 1 0 0 0 0 0 59 0 0 0 0 0 0 0 0 8 0 0 1 0 33 0
## 2021 0 1 1 0 0 0 13 0 0 0 0 0 0 0 0 21 0 0 24 1 10 1
## 2022 1 6 11 4 3 1 4 1 2 9 0 1 2 1 0 11 0 3 2 0 1 7
## 2023 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## 52 6 60 64 7 8 80 999
## 2020 0 0 0 0 0 0 0 0
## 2021 0 0 0 1 0 0 1 0
## 2022 1 0 2 0 0 0 0 12
## 2023 0 0 0 0 0 0 0 0
## 2024 0 0 0 0 0 0 0 0
df.mod$nb_sort_an <- as.numeric(df.mod$nb_sort_an)
df.mod$nb_sort_an_cat <- cut(df.mod$nb_sort_an, breaks=quantile(df.mod$nb_sort_an, probs=0:3/3, na.rm = T), include.lowest=TRUE, labels=c(
paste0("Q1 (<=",
#quantile(df.mod$nb_sort_an, probs=0:4/4, na.rm = T)[[1]], "-",
quantile(df.mod$nb_sort_an, probs=0:3/3, na.rm = T)[[2]],
")"),
paste0("Q2 (", quantile(df.mod$nb_sort_an, probs=0:3/3, na.rm = T)[[2]]+1, "-", quantile(df.mod$nb_sort_an, probs=0:3/3, na.rm = T)[[3]], ")"),
paste0("Q3 (>=", quantile(df.mod$nb_sort_an, probs=0:3/3, na.rm = T)[[3]]+1
,")") ))
unique(df.mod$nb_sort_an_cat); length(na.omit(df.mod$nb_sort_an_cat)) ; table(df.mod$nb_sort_an_cat) ; table(df.mod$a, df.mod$nb_sort_an_cat)
## [1] Q1 (<=15) Q2 (16-30) Q3 (>=31) <NA>
## Levels: Q1 (<=15) Q2 (16-30) Q3 (>=31)
## [1] 333
##
## Q1 (<=15) Q2 (16-30) Q3 (>=31)
## 174 77 82
##
## Q1 (<=15) Q2 (16-30) Q3 (>=31)
## 2020 93 8 1
## 2021 25 21 28
## 2022 31 24 30
## 2023 0 0 0
## 2024 0 0 0
# dépenses
# 1= "< 100 euros"; 2="entre 100-500 euros"; 3= "entre 500-1000 euros "; 4= "entre 1000-2000 euros ";5 ="supérieur à 2000"
table(df.mod$dep_pdb)
##
## 0 1 2 3 4 5 NA
## 167 88 51 19 4 4 176
table(df.mod$dep_pe)
##
## 0 1 2 3 4 5 NA
## 205 18 22 15 23 50 176
table(df.mod$dep_csm)
##
## 0 1 2 3 4 5 NA
## 300 10 16 3 3 1 176
table(df.mod$dep_po)
##
## 0 1 3 NA
## 299 33 1 176
df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")] <- lapply(df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], as.numeric)
## Warning in lapply(df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], : NAs
## introduits lors de la conversion automatique
## Warning in lapply(df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], : NAs
## introduits lors de la conversion automatique
## Warning in lapply(df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], : NAs
## introduits lors de la conversion automatique
## Warning in lapply(df.mod[, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")], : NAs
## introduits lors de la conversion automatique
df.mod$dep <- NA
df.mod$dep.median <- NA
df.mod$dep.median.rd <- NA
df.mod$dep_n <- NA
for (i in 1:nrow(df.mod)) {
#i=1
dep. <- as.vector(unlist(df.mod[i, c("dep_pdb", "dep_pe", "dep_csm", "dep_po")]))
sort(dep.[na.omit(dep.)!=0])
df.mod[i,"dep"] <- paste0(sort(dep.[na.omit(dep.)!=0]), collapse=",")
df.mod[i,"dep.median"] <- median(dep.[na.omit(dep.)!=0])
df.mod[i,"dep.median.rd"] <- ceiling(df.mod[i,"dep.median"])
df.mod[i,"dep_n"] <- length(na.omit(dep.[dep.!=0]))
}
rm(dep.,i)
table(df.mod$dep)
##
## 1 1,1 1,1,1,1 1,1,1,2 1,2 1,3 1,4 1,5 2
## 462 99 9 1 2 14 4 2 2 58
## 2,2 2,3 2,5 3 3,5 4 4,4 5 5,5
## 5 1 4 32 1 26 1 46 1
arrange(unique(df.mod[, c("mod_peche", "dep_pdb", "dep_pe", "dep_csm", "dep_po")]), mod_peche)
## mod_peche dep_pdb dep_pe dep_csm dep_po
## 1 chasse sous-marine 0 0 1 0
## 2 chasse sous-marine 0 0 2 0
## 3 chasse sous-marine 0 0 4 0
## 4 chasse sous-marine 0 0 3 0
## 5 chasse sous-marine NA NA NA NA
## 6 pdb, csm NA NA NA NA
## 7 peche à l'oursin 0 0 4 1
## 8 peche à l'oursin 0 0 2 1
## 9 peche du bord 2 0 0 0
## 10 peche du bord 1 0 0 0
## 11 peche du bord 4 0 0 0
## 12 peche du bord 3 0 0 0
## 13 peche du bord 1 0 0 1
## 14 peche du bord 5 0 0 0
## 15 peche du bord 1 0 1 0
## 16 peche du bord 2 5 0 0
## 17 peche du bord 2 0 1 0
## 18 peche du bord 3 0 2 0
## 19 peche du bord 1 3 0 0
## 20 peche du bord 2 0 2 0
## 21 peche du bord 2 2 0 0
## 22 peche du bord NA NA NA NA
## 23 peche embarquée 0 3 0 0
## 24 peche embarquée 0 4 0 0
## 25 peche embarquée 0 1 0 0
## 26 peche embarquée 0 5 0 0
## 27 peche embarquée 0 0 0 0
## 28 peche embarquée 0 2 0 0
## 29 peche embarquée 3 0 0 0
## 30 peche embarquée 0 5 0 1
## 31 peche embarquée 2 5 0 0
## 32 peche embarquée 0 5 2 0
## 33 peche embarquée 1 3 0 0
## 34 peche embarquée 3 5 0 0
## 35 peche embarquée 2 2 0 0
## 36 peche embarquée 2 0 0 0
## 37 peche embarquée 1 2 1 1
## 38 peche embarquée 0 4 4 0
## 39 peche embarquée 0 1 1 0
## 40 peche embarquée 0 5 5 0
## 41 peche embarquée NA NA NA NA
## 42 <NA> NA NA NA NA
## 43 <NA> 0 0 0 0
## 44 <NA> 1 0 0 1
## 45 <NA> 2 0 0 1
## 46 <NA> 2 0 0 0
## 47 <NA> 1 0 0 0
## 48 <NA> 3 0 0 1
## 49 <NA> 0 0 0 1
## 50 <NA> 0 0 0 3
## 51 <NA> 4 0 0 0
## 52 <NA> 5 0 0 0
## 53 <NA> 3 0 0 0
## 54 <NA> 4 0 0 1
## 55 <NA> 5 0 0 1
## 56 <NA> 1 0 2 0
## 57 <NA> 0 0 2 1
## 58 <NA> 1 1 2 1
## 59 <NA> 1 1 1 1
table(df.mod$dep.median.rd)
##
## 1 2 3 4 5
## 111 81 37 32 47
df.mod$dep.mod_peche <- NA
unique(df.mod$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## [5] pdb, csm <NA>
## 5 Levels: chasse sous-marine pdb, csm peche à l'oursin ... peche embarquée
table(df.mod$mod_peche)
##
## chasse sous-marine pdb, csm peche à l'oursin peche du bord
## 38 2 2 326
## peche embarquée
## 151
#for (i in 1:nrow(df.mod)) {
# if(df.mod[i,"mod_peche"] == "peche du bord") {
# df.mod[i,"dep.mod_peche"] <- df.mod[i,"dep_pdb"]
# } else if (df.mod[i,"mod_peche"] == "peche embarquée") {
# df.mod[i,"dep.mod_peche"] <- df.mod[i,"dep_pe"]
# } else if (df.mod[i,"mod_peche"] == "chasse sous-marine") {
# df.mod[i,"dep.mod_peche"] <- df.mod[i,"dep_csm"]
# } else if (df.mod[i,"mod_peche"] == "peche à l'oursin") {
# df.mod[i,"dep.mod_peche"] <- df.mod[i,"dep_po"]
# } else {
# df.mod[i,"dep.mod_peche"] <- NA
# }
#}
for (i in 1:nrow(df.mod)) {
df.mod[i,"dep.mod_peche"] <- ifelse(df.mod[i,"mod_peche"] == "peche du bord", df.mod[i,"dep_pdb"], df.mod[i,"dep.mod_peche"])
df.mod[i,"dep.mod_peche"] <- ifelse(df.mod[i,"mod_peche"] == "peche embarquée", df.mod[i,"dep_pe"], df.mod[i,"dep.mod_peche"])
df.mod[i,"dep.mod_peche"] <- ifelse(df.mod[i,"mod_peche"] == "chasse sous-marine", df.mod[i,"dep_csm"], df.mod[i,"dep.mod_peche"])
df.mod[i,"dep.mod_peche"] <- ifelse(df.mod[i,"mod_peche"] == "peche à l'oursin", df.mod[i,"dep_po"], df.mod[i,"dep.mod_peche"])
df.mod[i,"dep.mod_peche"] <- ifelse(df.mod[i,"mod_peche"] %notin% c("peche du bord", "peche embarquée", "chasse sous-marine", "peche à l'oursin"), NA, df.mod[i,"dep.mod_peche"])
}
df.mod[,c("mod_peche","dep_pdb", "dep_pe", "dep_csm", "dep_po", "dep.mod_peche")]
## mod_peche dep_pdb dep_pe dep_csm dep_po dep.mod_peche
## 1 peche du bord 2 0 0 0 2
## 2 chasse sous-marine 0 0 1 0 1
## 3 peche du bord 1 0 0 0 1
## 4 peche embarquée 0 3 0 0 3
## 5 peche embarquée 0 3 0 0 3
## 6 peche embarquée 0 4 0 0 4
## 7 peche embarquée 0 1 0 0 1
## 8 peche embarquée 0 5 0 0 5
## 9 peche du bord 2 0 0 0 2
## 10 peche du bord 1 0 0 0 1
## 11 peche du bord 1 0 0 0 1
## 12 peche du bord 1 0 0 0 1
## 13 chasse sous-marine 0 0 2 0 2
## 14 peche du bord 1 0 0 0 1
## 15 peche du bord 1 0 0 0 1
## 16 peche du bord 1 0 0 0 1
## 17 peche du bord 1 0 0 0 1
## 18 peche embarquée 0 0 0 0 0
## 19 peche embarquée 0 2 0 0 2
## 20 peche embarquée 0 5 0 0 5
## 21 peche embarquée 0 5 0 0 5
## 22 peche embarquée 0 1 0 0 1
## 23 chasse sous-marine 0 0 2 0 2
## 24 peche embarquée 0 2 0 0 2
## 25 peche embarquée 0 4 0 0 4
## 26 peche embarquée 0 4 0 0 4
## 27 peche embarquée 0 3 0 0 3
## 28 peche du bord 1 0 0 0 1
## 29 peche du bord 1 0 0 0 1
## 30 peche du bord 1 0 0 0 1
## 31 peche du bord 1 0 0 0 1
## 32 peche du bord 1 0 0 0 1
## 33 peche du bord 4 0 0 0 4
## 34 peche du bord 1 0 0 0 1
## 35 peche du bord 1 0 0 0 1
## 36 peche du bord 1 0 0 0 1
## 37 peche du bord 1 0 0 0 1
## 38 peche du bord 1 0 0 0 1
## 39 peche du bord 1 0 0 0 1
## 40 peche du bord 1 0 0 0 1
## 41 peche du bord 1 0 0 0 1
## 42 chasse sous-marine 0 0 1 0 1
## 43 peche du bord 1 0 0 0 1
## 44 peche du bord 1 0 0 0 1
## 45 peche embarquée 0 2 0 0 2
## 46 peche embarquée 0 2 0 0 2
## 47 peche embarquée 0 3 0 0 3
## 48 peche embarquée 0 1 0 0 1
## 49 peche embarquée 0 1 0 0 1
## 50 peche du bord 1 0 0 0 1
## 51 chasse sous-marine 0 0 2 0 2
## 52 peche du bord 1 0 0 0 1
## 53 peche du bord 1 0 0 0 1
## 54 peche du bord 1 0 0 0 1
## 55 peche du bord 1 0 0 0 1
## 56 peche du bord 1 0 0 0 1
## 57 peche du bord 1 0 0 0 1
## 58 peche du bord 1 0 0 0 1
## 59 peche du bord 1 0 0 0 1
## 60 chasse sous-marine 0 0 1 0 1
## 61 peche du bord 1 0 0 0 1
## 62 peche du bord 1 0 0 0 1
## 63 peche du bord 1 0 0 0 1
## 64 peche du bord 1 0 0 0 1
## 65 peche du bord 1 0 0 0 1
## 66 peche du bord 1 0 0 0 1
## 67 chasse sous-marine 0 0 2 0 2
## 68 peche du bord 1 0 0 0 1
## 69 peche du bord 2 0 0 0 2
## 70 peche du bord 1 0 0 0 1
## 71 peche du bord 2 0 0 0 2
## 72 peche du bord 1 0 0 0 1
## 73 peche du bord 1 0 0 0 1
## 74 peche embarquée 3 0 0 0 0
## 75 peche du bord 1 0 0 0 1
## 76 chasse sous-marine 0 0 2 0 2
## 77 peche du bord 1 0 0 0 1
## 78 peche du bord 1 0 0 0 1
## 79 chasse sous-marine 0 0 1 0 1
## 80 peche du bord 1 0 0 0 1
## 81 peche du bord 1 0 0 0 1
## 82 peche du bord 1 0 0 0 1
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## 680 <NA> NA NA NA NA NA
## 681 <NA> NA NA NA NA NA
## 682 <NA> NA NA NA NA NA
## 683 <NA> NA NA NA NA NA
## 684 <NA> NA NA NA NA NA
## 685 <NA> NA NA NA NA NA
## 686 <NA> NA NA NA NA NA
## 687 <NA> NA NA NA NA NA
## 688 <NA> NA NA NA NA NA
## 689 <NA> NA NA NA NA NA
## 690 <NA> NA NA NA NA NA
## 691 <NA> NA NA NA NA NA
## 692 <NA> NA NA NA NA NA
## 693 <NA> NA NA NA NA NA
## 694 <NA> NA NA NA NA NA
## 695 <NA> NA NA NA NA NA
## 696 <NA> NA NA NA NA NA
## 697 <NA> NA NA NA NA NA
## 698 <NA> NA NA NA NA NA
## 699 <NA> 0 0 0 0 NA
## 700 <NA> 0 0 0 0 NA
## 701 <NA> 1 0 0 1 NA
## 702 <NA> 2 0 0 1 NA
## 703 <NA> 2 0 0 0 NA
## 704 <NA> 0 0 0 0 NA
## 705 <NA> 0 0 0 0 NA
## 706 <NA> 1 0 0 0 NA
## 707 <NA> 3 0 0 1 NA
## 708 <NA> 1 0 0 1 NA
## 709 <NA> 1 0 0 1 NA
## 710 <NA> 2 0 0 0 NA
## 711 <NA> 0 0 0 0 NA
## 712 <NA> 0 0 0 0 NA
## 713 <NA> 0 0 0 1 NA
## 714 <NA> 1 0 0 0 NA
## 715 <NA> 0 0 0 3 NA
## 716 <NA> 2 0 0 1 NA
## 717 <NA> 2 0 0 0 NA
## 718 <NA> 0 0 0 0 NA
## 719 <NA> 0 0 0 1 NA
## 720 <NA> 4 0 0 0 NA
## 721 <NA> 0 0 0 0 NA
## 722 <NA> 1 0 0 0 NA
## 723 <NA> 0 0 0 0 NA
## 724 <NA> 0 0 0 0 NA
## 725 <NA> 0 0 0 0 NA
## 726 <NA> 0 0 0 0 NA
## 727 <NA> 0 0 0 0 NA
## 728 <NA> 0 0 0 0 NA
## 729 <NA> 1 0 0 0 NA
## 730 <NA> 0 0 0 0 NA
## 731 <NA> 0 0 0 0 NA
## 732 <NA> 0 0 0 1 NA
## 733 <NA> 5 0 0 0 NA
## 734 <NA> 3 0 0 0 NA
## 735 <NA> 1 0 0 1 NA
## 736 <NA> 2 0 0 0 NA
## 737 <NA> 0 0 0 0 NA
## 738 <NA> 0 0 0 1 NA
## 739 <NA> 2 0 0 0 NA
## 740 <NA> 3 0 0 0 NA
## 741 <NA> 0 0 0 1 NA
## 742 <NA> 0 0 0 0 NA
## 743 <NA> 2 0 0 1 NA
## 744 <NA> 1 0 0 0 NA
## 745 <NA> 3 0 0 1 NA
## 746 <NA> 2 0 0 1 NA
## 747 <NA> 1 0 0 1 NA
## 748 <NA> 4 0 0 1 NA
## 749 <NA> 2 0 0 1 NA
## 750 <NA> 0 0 0 0 NA
## 751 <NA> 2 0 0 0 NA
## 752 <NA> 2 0 0 1 NA
## 753 <NA> 0 0 0 1 NA
## 754 <NA> 1 0 0 1 NA
## 755 <NA> 5 0 0 1 NA
## 756 <NA> 0 0 0 0 NA
## 757 <NA> 0 0 0 0 NA
## 758 <NA> 2 0 0 1 NA
## 759 <NA> 0 0 0 0 NA
## 760 <NA> 0 0 0 0 NA
## 761 <NA> 0 0 0 0 NA
## 762 <NA> 4 0 0 0 NA
## 763 <NA> 2 0 0 1 NA
## 764 <NA> 2 0 0 0 NA
## 765 <NA> 2 0 0 1 NA
## 766 <NA> 3 0 0 0 NA
## 767 <NA> 1 0 2 0 NA
## 768 <NA> 0 0 2 1 NA
## 769 <NA> 1 1 2 1 NA
## 770 <NA> 1 1 1 1 NA
df.mod$dep.mod_peche <- ifelse(df.mod$dep.mod_peche == 0, NA, df.mod$dep.mod_peche)
unique(df.mod$dep.mod_peche); length(na.omit(df.mod$dep.mod_peche)) ; table(df.mod$dep.mod_peche) ; table(df.mod$a, df.mod$dep.mod_peche) #no data for 2023
## [1] 2 1 3 4 5 NA
## [1] 258
##
## 1 2 3 4 5
## 94 59 29 25 51
##
## 1 2 3 4 5
## 2020 70 17 4 5 4
## 2021 10 17 12 12 23
## 2022 14 25 13 8 24
## 2023 0 0 0 0 0
## 2024 0 0 0 0 0
# 1= "< 100 euros"; 2="entre 100-500 euros"; 3= "entre 500-1000 euros"; 4= "entre 1000-2000 euros";5 ="supérieur à 2000"
df.mod$dep.mod_peche.chr <- as.character(df.mod$dep.mod_peche)
df.mod$dep.mod_peche.chr <- ifelse(is.na(df.mod$dep.mod_peche.chr), "NA", df.mod$dep.mod_peche.chr)
for (i in 1:nrow(df.mod)) {
if (df.mod[i,"dep.mod_peche.chr"] %in% c("1", "2")) {
df.mod[i,"dep.mod_peche.chr"] <- "< 100-500 euros"
} else if (df.mod[i,"dep.mod_peche.chr"] %in% c("3", "4")) {
df.mod[i,"dep.mod_peche.chr"] <- "entre 500-2000 euros"
} else if (df.mod[i,"dep.mod_peche.chr"] == "5") {
df.mod[i,"dep.mod_peche.chr"] <- "> 2000 euros"
} else {
df.mod[i,"dep.mod_peche.chr"] <- NA
}
}
df.mod$dep.median.rd.chr <- as.character(df.mod$dep.median.rd)
df.mod$dep.median.rd.chr <- ifelse(is.na(df.mod$dep.median.rd.chr), "NA", df.mod$dep.median.rd.chr)
for (i in 1:nrow(df.mod)) {
if (df.mod[i,"dep.median.rd.chr"] %in% c("1", "2")) {
df.mod[i,"dep.median.rd.chr"] <- "< 100-500 euros"
} else if (df.mod[i,"dep.median.rd.chr"] %in% c("3", "4")) {
df.mod[i,"dep.median.rd.chr"] <- "entre 500-2000 euros"
} else if (df.mod[i,"dep.median.rd.chr"] == "5") {
df.mod[i,"dep.median.rd.chr"] <- "> 2000 euros"
} else {
df.mod[i,"dep.median.rd.chr"] <- NA
}
}
rm(i)
df.mod$a <- as.factor(df.mod$a)
df.mod$mod_peche <- as.factor(df.mod$mod_peche)
df.mod$age_classe <- as.factor(df.mod$age_classe)
df.mod$cat_pro.gp <- as.factor(df.mod$cat_pro.gp)
df.mod$nb_sort_an <- as.numeric(df.mod$nb_sort_an)
df.mod$classe_avis_pnm <- as.factor(df.mod$classe_avis_pnm)
df.mod$res_tour <- as.factor(df.mod$res_tour)
df.mod$poss_bat <- as.factor(df.mod$poss_bat)
df.mod$Temps_peche_estime.cat2h <- as.factor(df.mod$Temps_peche_estime.cat2h)
df.mod$Temps_peche_effectif.cat2h <- as.factor(df.mod$Temps_peche_effectif.cat2h)
df.mod$time.day.gp <- as.factor(df.mod$time.day.gp)
df.mod$zone.gp <- as.factor(df.mod$zone.gp)
df.mod$nb_sort_an_cat <- as.factor(df.mod$nb_sort_an_cat)
df.mod$dep.mod_peche.chr <- as.factor(df.mod$dep.mod_peche.chr)
df.mod$dep.median.rd.chr <- as.factor(df.mod$dep.median.rd.chr)
df.mod <- df.mod[, c("mod_peche"
#short
,"a"
,"res_tour"
,"Temps_peche_estime.cat2h"
,"zone.gp"
#large
,"age_classe"
,"cat_pro.gp"
,"poss_bat"
,"time.day.gp"
,"nb_sort_an_cat"
,"dep.mod_peche.chr"
,"classe_avis_pnm"
)]
df.mod %>% filter(mod_peche != "pdb, csm") -> df.mod
filter(df.mod, a != "2024") -> df.mod
filter(df.mod, mod_peche != "peche à l'oursin") -> df.mod
# Set the reference group for mod_peche bord to be peche du
df.mod$mod_peche <- relevel(df.mod$mod_peche, ref = "peche du bord")
df.mod <- droplevels(df.mod)
# model short
df.mod.short <- na.omit(df.mod[,c("mod_peche",
"a",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp")])
#saveRDS(df.mod.short, "df.mod.short.rds")
df.mod.short <- droplevels(df.mod.short)
df.mod.short <- data.frame(df.mod.short)
# Function to count observations for each level of a factor variable
count_levels <- function(df, var_name) {
df %>%
group_by(across(all_of(var_name))) %>%
summarise(count = n()) %>%
ungroup() %>%
arrange(desc(count))
}
# List of categorical variables to summarize
categorical_vars <- c("a", "res_tour", "Temps_peche_estime.cat2h", "zone.gp")
# Summarize counts for each categorical variable
summary_list <- lapply(categorical_vars, function(var) count_levels(df.mod.short, var))
# Display summaries
names(summary_list) <- categorical_vars
summary_list
## $a
## # A tibble: 4 × 2
## a count
## <fct> <int>
## 1 2023 171
## 2 2020 102
## 3 2022 84
## 4 2021 73
##
## $res_tour
## # A tibble: 2 × 2
## res_tour count
## <fct> <int>
## 1 resident 316
## 2 non-resident 114
##
## $Temps_peche_estime.cat2h
## # A tibble: 2 × 2
## Temps_peche_estime.cat2h count
## <fct> <int>
## 1 >=2h 380
## 2 <2h 50
##
## $zone.gp
## # A tibble: 4 × 2
## zone.gp count
## <fct> <int>
## 1 Est-Nord Cap 212
## 2 nimp_ou 126
## 3 Agriates_St-Florent 62
## 4 Ouest-Nord Cap 30
(count_table <- df.mod.short %>%
group_by(a, #sexe,
res_tour, Temps_peche_estime.cat2h, zone.gp) %>%
summarise(count = n()) %>%
ungroup())
## `summarise()` has grouped output by 'a', 'res_tour',
## 'Temps_peche_estime.cat2h'. You can override using the `.groups` argument.
## # A tibble: 49 × 5
## a res_tour Temps_peche_estime.cat2h zone.gp count
## <fct> <fct> <fct> <fct> <int>
## 1 2020 non-resident <2h Agriates_St-Florent 2
## 2 2020 non-resident <2h Est-Nord Cap 1
## 3 2020 non-resident >=2h Agriates_St-Florent 8
## 4 2020 non-resident >=2h Est-Nord Cap 18
## 5 2020 non-resident >=2h nimp_ou 1
## 6 2020 non-resident >=2h Ouest-Nord Cap 1
## 7 2020 resident <2h Agriates_St-Florent 2
## 8 2020 resident <2h Est-Nord Cap 6
## 9 2020 resident >=2h Agriates_St-Florent 8
## 10 2020 resident >=2h Est-Nord Cap 48
## # ℹ 39 more rows
multinom_model.short <- multinom(mod_peche ~ ., data = df.mod.short)
## # weights: 30 (18 variable)
## initial value 472.403284
## iter 10 value 307.689559
## iter 20 value 304.954087
## iter 30 value 304.750340
## final value 304.749833
## converged
summary(multinom_model.short)
## Call:
## multinom(formula = mod_peche ~ ., data = df.mod.short)
##
## Coefficients:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine -15.531556 -0.6772494 -0.8243492 -0.3905146
## peche embarquée -1.379239 1.6447327 1.2031141 -1.2150830
## res_tourresident Temps_peche_estime.cat2h>=2h
## chasse sous-marine -0.7185132 -0.6643333
## peche embarquée -0.2742922 1.2302534
## zone.gpEst-Nord Cap zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 15.0483917 15.571129 14.2762935
## peche embarquée -0.9123038 0.280247 -0.1056433
##
## Std. Errors:
## (Intercept) a2021 a2022 a2023 res_tourresident
## chasse sous-marine 0.5136046 0.8428932 0.7507818 0.4446096 0.3839879
## peche embarquée 0.5793119 0.3841305 0.3655204 0.3731758 0.2993513
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.4598554 0.3452578
## peche embarquée 0.4720958 0.3551526
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.4583714 0.8019845
## peche embarquée 0.3883840 0.5095204
##
## Residual Deviance: 609.4997
## AIC: 645.4997
#interpret the coefficients in terms of odds ratios
exp(coef(multinom_model.short))
## (Intercept) a2021 a2022 a2023 res_tourresident
## chasse sous-marine 1.797757e-07 0.5080124 0.4385203 0.6767086 0.4874765
## peche embarquée 2.517701e-01 5.1796250 3.3304721 0.2966854 0.7601099
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.5146165 3.431101e+06
## peche embarquée 3.4220967 4.015980e-01
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 5.787026e+06 1.585315e+06
## peche embarquée 1.323457e+00 8.997456e-01
(multinom.tbl.short <- tidy(multinom_model.short, conf.int = TRUE))
## # A tibble: 18 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -15.5 0.514 -30.2 7.00e-201 -16.5 -14.5
## 2 chasse sous-… a2021 -0.677 0.843 -0.803 4.22e- 1 -2.33 0.975
## 3 chasse sous-… a2022 -0.824 0.751 -1.10 2.72e- 1 -2.30 0.647
## 4 chasse sous-… a2023 -0.391 0.445 -0.878 3.80e- 1 -1.26 0.481
## 5 chasse sous-… res_… -0.719 0.384 -1.87 6.13e- 2 -1.47 0.0341
## 6 chasse sous-… Temp… -0.664 0.460 -1.44 1.49e- 1 -1.57 0.237
## 7 chasse sous-… zone… 15.0 0.345 43.6 0 14.4 15.7
## 8 chasse sous-… zone… 15.6 0.458 34.0 6.07e-253 14.7 16.5
## 9 chasse sous-… zone… 14.3 0.802 17.8 6.92e- 71 12.7 15.8
## 10 peche embarq… (Int… -1.38 0.579 -2.38 1.73e- 2 -2.51 -0.244
## 11 peche embarq… a2021 1.64 0.384 4.28 1.85e- 5 0.892 2.40
## 12 peche embarq… a2022 1.20 0.366 3.29 9.97e- 4 0.487 1.92
## 13 peche embarq… a2023 -1.22 0.373 -3.26 1.13e- 3 -1.95 -0.484
## 14 peche embarq… res_… -0.274 0.299 -0.916 3.60e- 1 -0.861 0.312
## 15 peche embarq… Temp… 1.23 0.472 2.61 9.16e- 3 0.305 2.16
## 16 peche embarq… zone… -0.912 0.355 -2.57 1.02e- 2 -1.61 -0.216
## 17 peche embarq… zone… 0.280 0.388 0.722 4.71e- 1 -0.481 1.04
## 18 peche embarq… zone… -0.106 0.510 -0.207 8.36e- 1 -1.10 0.893
(multinom.tbl.short.sign <- filter(multinom.tbl.short, p.value < 0.05))
## # A tibble: 10 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -15.5 0.514 -30.2 7.00e-201 -16.5 -14.5
## 2 chasse sous-… zone… 15.0 0.345 43.6 0 14.4 15.7
## 3 chasse sous-… zone… 15.6 0.458 34.0 6.07e-253 14.7 16.5
## 4 chasse sous-… zone… 14.3 0.802 17.8 6.92e- 71 12.7 15.8
## 5 peche embarq… (Int… -1.38 0.579 -2.38 1.73e- 2 -2.51 -0.244
## 6 peche embarq… a2021 1.64 0.384 4.28 1.85e- 5 0.892 2.40
## 7 peche embarq… a2022 1.20 0.366 3.29 9.97e- 4 0.487 1.92
## 8 peche embarq… a2023 -1.22 0.373 -3.26 1.13e- 3 -1.95 -0.484
## 9 peche embarq… Temp… 1.23 0.472 2.61 9.16e- 3 0.305 2.16
## 10 peche embarq… zone… -0.912 0.355 -2.57 1.02e- 2 -1.61 -0.216
#Messages d'avis :
#1: Dans sqrt(diag(vc)) : Production de NaN
#2: Dans sqrt(diag(vcov(object))) : Production de NaN
# All of the observations are zero for some combination of factors. Thus any coefficient that involves a comparison with this state will have a parameter value of large magnitude (i.e. abs(beta) >> 1); it should theoretically be infinite, but is usually somewhere between 10 and 30 (depending on where the numerical methods give up). These coefficients will either have ridiculously large standard errors and (Wald) confidence intervals, or (as in your case) NaN values (https://stackoverflow.com/questions/67338560/zeroinfl-model-warning-message-in-sqrtdiagobjectvcov-nans-produced)
#https://www.youtube.com/@bkrai
#https://www.youtube.com/watch?v=S2rZp4L_nXo
#https://www.youtube.com/watch?v=oxRy2DMrOF4
#https://www.youtube.com/watch?v=11VY8CmNVDQ
#https://www.youtube.com/watch?v=POyTaeneHJY
#2-tailed Z-test (idem result than with above tidy function on model)
z <- summary(multinom_model.short)$coefficient/summary(multinom_model.short)$standard.errors
(p <- (1 - pnorm(abs(z), 0, 1)) * 2)
## (Intercept) a2021 a2022 a2023
## chasse sous-marine 0.00000000 4.216963e-01 0.2722098874 0.379763853
## peche embarquée 0.01727402 1.854684e-05 0.0009965096 0.001129695
## res_tourresident Temps_peche_estime.cat2h>=2h
## chasse sous-marine 0.06131913 0.148554225
## peche embarquée 0.35951554 0.009162246
## zone.gpEst-Nord Cap zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.00000000 0.0000000 0.0000000
## peche embarquée 0.01020615 0.4705578 0.8357454
multinom_model.short.sign <- multinom(mod_peche ~ . - res_tour, data = df.mod.short)
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
summary(multinom_model.short.sign)
## Call:
## multinom(formula = mod_peche ~ . - res_tour, data = df.mod.short)
##
## Coefficients:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine -15.367832 -0.7801757 -0.7506372 -0.2855243
## peche embarquée -1.530121 1.5864223 1.1977612 -1.2030551
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine -0.681608 14.3955317
## peche embarquée 1.200534 -0.9234898
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 14.7800302 13.7046384
## peche embarquée 0.2366787 -0.1120297
##
## Std. Errors:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine 0.4728258 0.8365691 0.7449720 0.4385730
## peche embarquée 0.5568326 0.3773443 0.3646674 0.3727123
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.4555603 0.3361120
## peche embarquée 0.4694631 0.3556158
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.4343721 0.7977725
## peche embarquée 0.3858984 0.5108607
##
## Residual Deviance: 613.3135
## AIC: 645.3135
z <- summary(multinom_model.short.sign)$coefficient/summary(multinom_model.short.sign)$standard.errors
(p <- (1 - pnorm(abs(z), 0, 1)) * 2)
## (Intercept) a2021 a2022 a2023
## chasse sous-marine 0.000000000 3.510319e-01 0.313644325 0.515026868
## peche embarquée 0.005997805 2.620332e-05 0.001021523 0.001247295
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.13460226 0.000000000
## peche embarquée 0.01055039 0.009407615
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.0000000 0.0000000
## peche embarquée 0.5396656 0.8264195
table(df.mod.short$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 248 37 145
# Data partition and modeling
set.seed(222)
ind <- sample(2, nrow(df.mod.short), replace = T, prob = c(.6,.4))
training <- df.mod.short[ind==1,]
testing <- df.mod.short[ind==2,]
table(training$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 144 24 86
table(testing$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 104 13 59
multinom_model.training <- multinom(mod_peche ~ . - res_tour, data = training)
## # weights: 27 (16 variable)
## initial value 279.047521
## iter 10 value 189.316988
## iter 20 value 184.085124
## iter 30 value 183.984067
## final value 183.975420
## converged
# Confusion matrix and misclassification error - training data
(p <- predict(multinom_model.training, training))
## [1] peche du bord peche du bord peche du bord peche embarquée
## [5] peche embarquée peche du bord peche du bord peche du bord
## [9] peche du bord peche du bord peche embarquée peche embarquée
## [13] peche embarquée peche embarquée peche du bord peche du bord
## [17] peche du bord peche du bord peche du bord peche du bord
## [21] peche du bord peche du bord peche du bord peche du bord
## [25] peche du bord peche du bord peche embarquée peche du bord
## [29] peche du bord peche du bord peche du bord peche embarquée
## [33] peche du bord peche du bord peche du bord peche du bord
## [37] peche du bord peche du bord peche du bord peche du bord
## [41] peche du bord peche du bord peche embarquée peche du bord
## [45] peche du bord peche du bord peche du bord peche du bord
## [49] peche du bord peche du bord peche du bord peche du bord
## [53] peche du bord peche du bord peche du bord peche embarquée
## [57] peche du bord peche du bord peche embarquée peche embarquée
## [61] peche embarquée peche embarquée peche embarquée peche embarquée
## [65] peche embarquée peche embarquée peche embarquée peche embarquée
## [69] peche embarquée peche embarquée peche embarquée peche embarquée
## [73] peche embarquée peche embarquée peche embarquée peche embarquée
## [77] peche embarquée peche embarquée peche embarquée peche embarquée
## [81] peche embarquée peche embarquée peche embarquée peche embarquée
## [85] peche embarquée peche embarquée peche embarquée peche embarquée
## [89] peche embarquée peche embarquée peche embarquée peche du bord
## [93] peche embarquée peche embarquée peche embarquée peche embarquée
## [97] peche embarquée peche embarquée peche embarquée peche embarquée
## [101] peche embarquée peche du bord peche embarquée peche du bord
## [105] peche embarquée peche embarquée peche du bord peche embarquée
## [109] peche embarquée peche du bord peche du bord peche du bord
## [113] peche embarquée peche du bord peche embarquée peche embarquée
## [117] peche embarquée peche embarquée peche embarquée peche embarquée
## [121] peche embarquée peche embarquée peche embarquée peche du bord
## [125] peche embarquée peche embarquée peche embarquée peche embarquée
## [129] peche embarquée peche embarquée peche embarquée peche embarquée
## [133] peche embarquée peche embarquée peche embarquée peche embarquée
## [137] peche embarquée peche embarquée peche du bord peche du bord
## [141] peche du bord peche du bord peche embarquée peche embarquée
## [145] peche embarquée peche embarquée peche embarquée peche embarquée
## [149] peche embarquée peche embarquée peche embarquée peche du bord
## [153] peche du bord peche du bord peche du bord peche du bord
## [157] peche du bord peche du bord peche du bord peche du bord
## [161] peche du bord peche du bord peche du bord peche du bord
## [165] peche du bord peche du bord peche du bord peche du bord
## [169] peche du bord peche du bord peche du bord peche du bord
## [173] peche du bord peche du bord peche du bord peche du bord
## [177] peche du bord peche du bord peche du bord peche du bord
## [181] peche du bord peche du bord peche du bord peche du bord
## [185] peche du bord peche du bord peche du bord peche du bord
## [189] peche du bord peche du bord peche du bord peche du bord
## [193] peche du bord peche du bord peche du bord peche du bord
## [197] peche du bord peche du bord peche du bord peche du bord
## [201] peche du bord peche du bord peche du bord peche du bord
## [205] peche du bord peche du bord peche du bord peche du bord
## [209] peche du bord peche du bord peche du bord peche du bord
## [213] peche du bord peche du bord peche du bord peche du bord
## [217] peche du bord peche du bord peche du bord peche du bord
## [221] peche du bord peche du bord peche du bord peche du bord
## [225] peche du bord peche du bord peche du bord peche du bord
## [229] peche du bord peche du bord peche du bord peche du bord
## [233] peche du bord peche du bord peche du bord peche du bord
## [237] peche du bord peche du bord peche du bord peche du bord
## [241] peche du bord peche du bord peche du bord peche du bord
## [245] peche du bord peche du bord peche du bord peche du bord
## [249] peche du bord peche du bord peche du bord peche du bord
## [253] peche du bord peche du bord
## Levels: peche du bord chasse sous-marine peche embarquée
(tab <- table(p, training$mod_peche))
##
## p peche du bord chasse sous-marine peche embarquée
## peche du bord 116 22 26
## chasse sous-marine 0 0 0
## peche embarquée 28 2 60
1 - sum(diag(tab))/sum(tab) # misclassification
## [1] 0.3070866
# Confusion matrix and misclassification error - testing data
(p1 <- predict(multinom_model.training, testing))
## [1] peche du bord peche du bord peche du bord peche du bord
## [5] peche du bord peche embarquée peche du bord peche du bord
## [9] peche du bord peche du bord peche du bord peche du bord
## [13] peche du bord peche du bord peche du bord peche du bord
## [17] peche du bord peche du bord peche embarquée peche embarquée
## [21] peche embarquée peche du bord peche du bord peche du bord
## [25] peche du bord peche du bord peche du bord peche du bord
## [29] peche du bord peche du bord peche du bord peche du bord
## [33] peche du bord peche du bord peche du bord peche du bord
## [37] peche embarquée peche embarquée peche du bord peche du bord
## [41] peche du bord peche du bord peche du bord peche du bord
## [45] peche embarquée peche embarquée peche embarquée peche embarquée
## [49] peche embarquée peche embarquée peche embarquée peche embarquée
## [53] peche embarquée peche embarquée peche embarquée peche embarquée
## [57] peche embarquée peche embarquée peche embarquée peche embarquée
## [61] peche embarquée peche embarquée peche embarquée peche embarquée
## [65] peche embarquée peche embarquée peche embarquée peche embarquée
## [69] peche embarquée peche embarquée peche embarquée peche embarquée
## [73] peche embarquée peche embarquée peche embarquée peche du bord
## [77] peche embarquée peche du bord peche du bord peche embarquée
## [81] peche embarquée peche embarquée peche embarquée peche embarquée
## [85] peche du bord peche embarquée peche du bord peche embarquée
## [89] peche embarquée peche embarquée peche embarquée peche embarquée
## [93] peche embarquée peche embarquée peche du bord peche du bord
## [97] peche embarquée peche du bord peche embarquée peche du bord
## [101] peche embarquée peche embarquée peche embarquée peche du bord
## [105] peche embarquée peche embarquée peche embarquée peche embarquée
## [109] peche du bord peche du bord peche du bord peche du bord
## [113] peche du bord peche du bord peche du bord peche du bord
## [117] peche du bord peche du bord peche du bord peche du bord
## [121] peche du bord peche du bord peche du bord peche du bord
## [125] peche du bord peche du bord peche du bord peche du bord
## [129] peche du bord peche du bord peche du bord peche du bord
## [133] peche du bord peche du bord peche du bord peche du bord
## [137] peche du bord peche du bord peche du bord peche du bord
## [141] peche du bord peche du bord peche du bord peche du bord
## [145] peche du bord peche du bord peche du bord peche du bord
## [149] peche du bord peche du bord peche du bord peche du bord
## [153] peche du bord peche du bord peche du bord peche du bord
## [157] peche du bord peche du bord peche du bord peche du bord
## [161] peche du bord peche du bord peche du bord peche du bord
## [165] peche du bord peche du bord peche du bord peche du bord
## [169] peche du bord peche du bord peche du bord peche du bord
## [173] peche du bord peche du bord peche du bord peche du bord
## Levels: peche du bord chasse sous-marine peche embarquée
(tab1 <- table(p1, testing$mod_peche))
##
## p1 peche du bord chasse sous-marine peche embarquée
## peche du bord 88 10 18
## chasse sous-marine 0 0 0
## peche embarquée 16 3 41
1 - sum(diag(tab1))/sum(tab1) # misclassification
## [1] 0.2670455
tab/colSums(tab)
##
## p peche du bord chasse sous-marine peche embarquée
## peche du bord 0.80555556 0.15277778 0.18055556
## chasse sous-marine 0.00000000 0.00000000 0.00000000
## peche embarquée 0.32558140 0.02325581 0.69767442
tab1/colSums(tab1)
##
## p1 peche du bord chasse sous-marine peche embarquée
## peche du bord 0.84615385 0.09615385 0.17307692
## chasse sous-marine 0.00000000 0.00000000 0.00000000
## peche embarquée 0.27118644 0.05084746 0.69491525
# obviously I do not have enough data in chasse sous-marine class !!
# Check assumptions for multinomial logistic regression:
#Assumption 1: Independence of observations.
#Assumption 2: Independence of Irrelevant Alternatives (IIA); i.e. Categories of the outcome variable must be mutually exclusive and exhaustive.
#Use the Hausman-McFadden test to check the IIA assumption. However, this test is not directly available in R, so we'll use an approximation.
# IIA assumption check
iia_test <- function(model, data, formula) {
reduced_model <- update(model, . ~ . - predictor1) # Example, modify as needed
model_ll <- logLik(model)
reduced_model_ll <- logLik(reduced_model)
chi_square <- 2 * (model_ll - reduced_model_ll)
p_value <- pchisq(chi_square, df = length(coef(model)) - length(coef(reduced_model)), lower.tail = FALSE)
return(p_value)
}
iia_result <- iia_test(model = multinom_model.short, data = df.mod.short, mod_peche ~ a + res_tour + Temps_peche_estime.cat2h + zone.gp)
## # weights: 30 (18 variable)
## initial value 472.403284
## iter 10 value 307.689559
## iter 20 value 304.954087
## iter 30 value 304.750340
## final value 304.749833
## converged
print(iia_result)
## 'log Lik.' 1 (df=18)
#Assumption 3: No Multicollinearity between independent variables.
#Check multicollinearity using the Variance Inflation Factor (VIF).
vif_results <- vif(multinom_model.short)
## Warning in vif.default(multinom_model.short): No intercept: vifs may not be
## sensible.
print(vif_results)
## GVIF Df GVIF^(1/(2*Df))
## a -4.896550e+02 3 NaN
## res_tour 3.031124e+00 1 1.7410125
## Temps_peche_estime.cat2h 4.028748e-01 1 0.6347242
## zone.gp -2.027990e+16 3 NaN
#Warning message
#glm.fit: algorithm did not converge
#This warning often occurs when you attempt to fit a logistic regression model in R and you experience perfect separation – that is, a predictor variable is able to perfectly separate the response variable into 0’s and 1’s. (https://www.statology.org/glm-fit-algorithm-did-not-converge/)
labels = rownames(coefficients(multinom_model.short))
ref = setdiff(multinom_model.short$lab,labels)
t(sapply(labels,function(i){
dat = df.mod.short
dat$mod_peche = as.numeric(dat$mod_peche == i)
vif.i <<- vif(glm(mod_peche ~ .,data=dat,family="binomial"))
}))
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## chasse sous-marine 1.337288 1.064174 1.038537 1.337524 3 1 1 3
## peche embarquée 1.304235 1.080600 1.035336 1.262823 3 1 1 3
## [,9] [,10] [,11] [,12]
## chasse sous-marine 1.049633 1.031588 1.019087 1.049664
## peche embarquée 1.045264 1.039519 1.017514 1.039658
#Assumption 4: Linearity in the logit (for continuous variables); i.e. Linear relationship between continuous variables and the logit transformation of the outcome variable.
#Assumption 5: No outliers or highly influential points.
#Also, absolute minimum of cases or multinomial logistic regression indicates a minimum of 10 cases per independent variable.
# stepwize regression for Multinomial Logistic Regression Model. (http://www.sthda.com/english/articles/36-classification-methods-essentials/150-stepwise-logistic-regression-essentials-in-r/)
# the null model contains only the intercept; the full model contains all predictors
(null_model <- multinom(mod_peche ~ 1, data = df.mod.short))
## # weights: 6 (2 variable)
## initial value 472.403284
## iter 10 value 384.866958
## iter 10 value 384.866955
## iter 10 value 384.866955
## final value 384.866955
## converged
## Call:
## multinom(formula = mod_peche ~ 1, data = df.mod.short)
##
## Coefficients:
## (Intercept)
## chasse sous-marine -1.9024938
## peche embarquée -0.5366879
##
## Residual Deviance: 769.7339
## AIC: 773.7339
(multinom_model.short)
## Call:
## multinom(formula = mod_peche ~ ., data = df.mod.short)
##
## Coefficients:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine -15.531556 -0.6772494 -0.8243492 -0.3905146
## peche embarquée -1.379239 1.6447327 1.2031141 -1.2150830
## res_tourresident Temps_peche_estime.cat2h>=2h
## chasse sous-marine -0.7185132 -0.6643333
## peche embarquée -0.2742922 1.2302534
## zone.gpEst-Nord Cap zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 15.0483917 15.571129 14.2762935
## peche embarquée -0.9123038 0.280247 -0.1056433
##
## Residual Deviance: 609.4997
## AIC: 645.4997
# use the stepAIC function from the MASS package, which performs both forward and backward stepwise selection based on AIC (Akaike Information Criterion)
stepwise_model.forward <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.short), direction = "both")
## Start: AIC=773.73
## mod_peche ~ 1
##
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## iter 10 value 382.078492
## iter 10 value 382.078492
## final value 382.078492
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## final value 379.691071
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 360.847747
## final value 359.845911
## converged
## Df AIC
## + a 6 668.27
## + zone.gp 6 735.69
## + Temps_peche_estime.cat2h 2 767.38
## + res_tour 2 772.16
## <none> 773.73
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
##
## Step: AIC=668.27
## mod_peche ~ a
##
## # weights: 6 (2 variable)
## initial value 472.403284
## iter 10 value 384.866958
## iter 10 value 384.866955
## iter 10 value 384.866955
## final value 384.866955
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 325.101218
## final value 324.998609
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 321.695267
## final value 321.588016
## converged
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
## Df AIC
## + zone.gp 6 652.01
## + Temps_peche_estime.cat2h 2 663.18
## <none> 668.27
## + res_tour 2 670.00
## - a 6 773.73
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
##
## Step: AIC=652.01
## mod_peche ~ a + zone.gp
##
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 360.847747
## final value 359.845911
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 312.200621
## iter 20 value 310.228279
## iter 30 value 310.189541
## final value 310.189494
## converged
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
## Df AIC
## + Temps_peche_estime.cat2h 2 645.31
## <none> 652.01
## + res_tour 2 652.38
## - zone.gp 6 668.27
## - a 6 735.69
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
##
## Step: AIC=645.31
## mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h
##
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 355.800103
## iter 20 value 354.671382
## final value 354.667727
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 321.695267
## final value 321.588016
## converged
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
## # weights: 30 (18 variable)
## initial value 472.403284
## iter 10 value 307.689559
## iter 20 value 304.954087
## iter 30 value 304.750340
## final value 304.749833
## converged
## Df AIC
## <none> 645.31
## + res_tour 2 645.50
## - Temps_peche_estime.cat2h 2 652.01
## - zone.gp 6 663.18
## - a 6 729.34
stepwise_model.forward$call
## multinom(formula = mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h,
## data = df.mod.short)
stepwise_model.backward <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.short), direction = "backward")
## Start: AIC=773.73
## mod_peche ~ 1
stepwise_model.backward$call
## multinom(formula = mod_peche ~ 1, data = df.mod.short)
stepwise_model.both <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.short), direction = "both")
## Start: AIC=773.73
## mod_peche ~ 1
##
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## iter 10 value 382.078492
## iter 10 value 382.078492
## final value 382.078492
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## final value 379.691071
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 360.847747
## final value 359.845911
## converged
## Df AIC
## + a 6 668.27
## + zone.gp 6 735.69
## + Temps_peche_estime.cat2h 2 767.38
## + res_tour 2 772.16
## <none> 773.73
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
##
## Step: AIC=668.27
## mod_peche ~ a
##
## # weights: 6 (2 variable)
## initial value 472.403284
## iter 10 value 384.866958
## iter 10 value 384.866955
## iter 10 value 384.866955
## final value 384.866955
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 325.101218
## final value 324.998609
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 321.695267
## final value 321.588016
## converged
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
## Df AIC
## + zone.gp 6 652.01
## + Temps_peche_estime.cat2h 2 663.18
## <none> 668.27
## + res_tour 2 670.00
## - a 6 773.73
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
##
## Step: AIC=652.01
## mod_peche ~ a + zone.gp
##
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 360.847747
## final value 359.845911
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 312.200621
## iter 20 value 310.228279
## iter 30 value 310.189541
## final value 310.189494
## converged
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
## Df AIC
## + Temps_peche_estime.cat2h 2 645.31
## <none> 652.01
## + res_tour 2 652.38
## - zone.gp 6 668.27
## - a 6 735.69
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
##
## Step: AIC=645.31
## mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h
##
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 355.800103
## iter 20 value 354.671382
## final value 354.667727
## converged
## # weights: 18 (10 variable)
## initial value 472.403284
## iter 10 value 321.695267
## final value 321.588016
## converged
## # weights: 24 (14 variable)
## initial value 472.403284
## iter 10 value 314.616096
## iter 20 value 312.025815
## iter 30 value 312.003990
## iter 30 value 312.003990
## final value 312.003990
## converged
## # weights: 30 (18 variable)
## initial value 472.403284
## iter 10 value 307.689559
## iter 20 value 304.954087
## iter 30 value 304.750340
## final value 304.749833
## converged
## Df AIC
## <none> 645.31
## + res_tour 2 645.50
## - Temps_peche_estime.cat2h 2 652.01
## - zone.gp 6 663.18
## - a 6 729.34
stepwise_model.both$call
## multinom(formula = mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h,
## data = df.mod.short)
stepwise_model.forward$call
## multinom(formula = mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h,
## data = df.mod.short)
stepwise_model.backward$call
## multinom(formula = mod_peche ~ 1, data = df.mod.short)
stepwise_model.both$call
## multinom(formula = mod_peche ~ a + zone.gp + Temps_peche_estime.cat2h,
## data = df.mod.short)
# Custom Stepwise Function for Multinomial Logistic Regression
stepwise_multinom <- function(data, response, predictors) {
# Helper function to calculate AIC for a given set of predictors
calculate_aic <- function(predictors) {
formula <- as.formula(paste(response, "~", paste(predictors, collapse = "+")))
model <- multinom(formula, data = data)
return(AIC(model))
}
best_aic <- Inf
best_model <- NULL
current_predictors <- c()
# Forward selection
for (predictor in predictors) {
new_predictors <- c(current_predictors, predictor)
new_aic <- calculate_aic(new_predictors)
if (new_aic < best_aic) {
best_aic <- new_aic
best_model <- new_predictors
}
}
# Backward elimination
improved <- TRUE
while (improved) {
improved <- FALSE
for (predictor in best_model) {
new_predictors <- setdiff(best_model, predictor)
if (length(new_predictors) == 0) break
new_aic <- calculate_aic(new_predictors)
if (new_aic < best_aic) {
best_aic <- new_aic
best_model <- new_predictors
improved <- TRUE
break
}
}
}
# Fit the final model with the selected predictors
final_formula <- as.formula(paste(response, "~", paste(best_model, collapse = "+")))
final_model <- multinom(final_formula, data = data)
return(list(model = final_model, predictors = best_model))
}
stepwise_multinom(data = df.mod.short, response = "mod_peche", predictors = c("a", "res_tour", "Temps_peche_estime.cat2h", "zone.gp"))
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## iter 10 value 382.078492
## iter 10 value 382.078492
## final value 382.078492
## converged
## # weights: 9 (4 variable)
## initial value 472.403284
## final value 379.691071
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 360.847747
## final value 359.845911
## converged
## # weights: 15 (8 variable)
## initial value 472.403284
## iter 10 value 332.894552
## final value 326.134634
## converged
## $model
## Call:
## multinom(formula = final_formula, data = data)
##
## Coefficients:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine -1.806767 -0.5447012 -0.4619273 -0.02392492
## peche embarquée -1.026629 1.8941165 1.6105646 -0.90413880
##
## Residual Deviance: 652.2693
## AIC: 668.2693
##
## $predictors
## [1] "a"
# fit with variables that have a significant effect on the dependant variable mod_peche
multinom_model.short.red <- multinom(mod_peche ~ . - res_tour, data = df.mod.short)
## # weights: 27 (16 variable)
## initial value 472.403284
## iter 10 value 308.487671
## iter 20 value 306.690569
## iter 30 value 306.656812
## final value 306.656762
## converged
summary(multinom_model.short.red)
## Call:
## multinom(formula = mod_peche ~ . - res_tour, data = df.mod.short)
##
## Coefficients:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine -15.367832 -0.7801757 -0.7506372 -0.2855243
## peche embarquée -1.530121 1.5864223 1.1977612 -1.2030551
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine -0.681608 14.3955317
## peche embarquée 1.200534 -0.9234898
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 14.7800302 13.7046384
## peche embarquée 0.2366787 -0.1120297
##
## Std. Errors:
## (Intercept) a2021 a2022 a2023
## chasse sous-marine 0.4728258 0.8365691 0.7449720 0.4385730
## peche embarquée 0.5568326 0.3773443 0.3646674 0.3727123
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.4555603 0.3361120
## peche embarquée 0.4694631 0.3556158
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.4343721 0.7977725
## peche embarquée 0.3858984 0.5108607
##
## Residual Deviance: 613.3135
## AIC: 645.3135
#interpret the coefficients in terms of odds ratios
exp(coef(multinom_model.short.red))
## (Intercept) a2021 a2022 a2023
## chasse sous-marine 2.117558e-07 0.4583255 0.4720656 0.7516201
## peche embarquée 2.165094e-01 4.8862360 3.3126922 0.3002754
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.505803 1.786076e+06
## peche embarquée 3.321889 3.971307e-01
## zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 2.623527e+06 8.950532e+05
## peche embarquée 1.267034e+00 8.940177e-01
(multinom.tbl.short.red <- tidy(multinom_model.short.red, conf.int = TRUE))
## # A tibble: 16 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -15.4 0.473 -32.5 9.96e-232 -16.3 -14.4
## 2 chasse sous-… a2021 -0.780 0.837 -0.933 3.51e- 1 -2.42 0.859
## 3 chasse sous-… a2022 -0.751 0.745 -1.01 3.14e- 1 -2.21 0.709
## 4 chasse sous-… a2023 -0.286 0.439 -0.651 5.15e- 1 -1.15 0.574
## 5 chasse sous-… Temp… -0.682 0.456 -1.50 1.35e- 1 -1.57 0.211
## 6 chasse sous-… zone… 14.4 0.336 42.8 0 13.7 15.1
## 7 chasse sous-… zone… 14.8 0.434 34.0 9.13e-254 13.9 15.6
## 8 chasse sous-… zone… 13.7 0.798 17.2 3.84e- 66 12.1 15.3
## 9 peche embarq… (Int… -1.53 0.557 -2.75 6.00e- 3 -2.62 -0.439
## 10 peche embarq… a2021 1.59 0.377 4.20 2.62e- 5 0.847 2.33
## 11 peche embarq… a2022 1.20 0.365 3.28 1.02e- 3 0.483 1.91
## 12 peche embarq… a2023 -1.20 0.373 -3.23 1.25e- 3 -1.93 -0.473
## 13 peche embarq… Temp… 1.20 0.469 2.56 1.06e- 2 0.280 2.12
## 14 peche embarq… zone… -0.923 0.356 -2.60 9.41e- 3 -1.62 -0.226
## 15 peche embarq… zone… 0.237 0.386 0.613 5.40e- 1 -0.520 0.993
## 16 peche embarq… zone… -0.112 0.511 -0.219 8.26e- 1 -1.11 0.889
write.csv2(multinom.tbl.short.red, "Tables/Regression/multinom.2020-2023.csv", row.names = F)
(multinom.tbl.short.red.sign <- filter(multinom.tbl.short.red, p.value < 0.05))
## # A tibble: 10 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -15.4 0.473 -32.5 9.96e-232 -16.3 -14.4
## 2 chasse sous-… zone… 14.4 0.336 42.8 0 13.7 15.1
## 3 chasse sous-… zone… 14.8 0.434 34.0 9.13e-254 13.9 15.6
## 4 chasse sous-… zone… 13.7 0.798 17.2 3.84e- 66 12.1 15.3
## 5 peche embarq… (Int… -1.53 0.557 -2.75 6.00e- 3 -2.62 -0.439
## 6 peche embarq… a2021 1.59 0.377 4.20 2.62e- 5 0.847 2.33
## 7 peche embarq… a2022 1.20 0.365 3.28 1.02e- 3 0.483 1.91
## 8 peche embarq… a2023 -1.20 0.373 -3.23 1.25e- 3 -1.93 -0.473
## 9 peche embarq… Temp… 1.20 0.469 2.56 1.06e- 2 0.280 2.12
## 10 peche embarq… zone… -0.923 0.356 -2.60 9.41e- 3 -1.62 -0.226
# watch video https://www.youtube.com/watch?v=oxRy2DMrOF4 on how to write the model to add it in a report
(mod1vs2 <- paste0("ln[P(mod_peche=2)/P(mod_peche=1)] = ", (exp(coef(multinom_model.short.red)))[1,1], " + " , (exp(coef(multinom_model.short.red)))[1,2],"*",colnames(exp(coef(multinom_model.short.red)))[2], " + ", (exp(coef(multinom_model.short.red)))[1,3],"*",colnames(exp(coef(multinom_model.short.red)))[3], " + ..."))
## [1] "ln[P(mod_peche=2)/P(mod_peche=1)] = 2.11755769117821e-07 + 0.458325463228916*a2021 + 0.472065644250823*a2022 + ..."
writeLines(mod1vs2, "Tables/Regression/multinom.2020-2023.P1vsP2.txt")
(mod1vs3 <- paste0("ln[P(mod_peche=3)/P(mod_peche=1)] = ", (exp(coef(multinom_model.short.red)))[2,1], " + " , (exp(coef(multinom_model.short.red)))[2,2],"*",colnames(exp(coef(multinom_model.short.red)))[2], " + ", (exp(coef(multinom_model.short.red)))[2,3],"*",colnames(exp(coef(multinom_model.short.red)))[3], " + ..."))
## [1] "ln[P(mod_peche=3)/P(mod_peche=1)] = 0.216509433062587 + 4.88623600845851*a2021 + 3.31269220130357*a2022 + ..."
writeLines(mod1vs3, "Tables/Regression/multinom.2020-2023.P1vsP3.txt")
# Fit a decision tree
# http://www.milbo.org/rpart-plot/prp.pdf
tree_model <- rpart(mod_peche ~ . - res_tour, data = df.mod.short, method = "class")
rpart.plot(tree_model, type = 4, extra = 2)
#ggsave("Figs/Tree/tree_2020-2023.png", width = 7, height = 4) #doesn't save the plot with ggsave !
# Open a PNG device
#png("Figs/Tree/tree_2020-2023.png", width = 600, height = 350) # bad resolution, save it manually
# Plot the decision tree
#rpart.plot(tree_model, type = 4, extra = 2)
# Close the device
#dev.off()
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red")))
# model large
df.mod.large <- na.omit(df.mod)
df.mod.large <- droplevels(df.mod.large)
df.mod.large <- data.frame(df.mod.large)
# Function to count observations for each level of a factor variable
count_levels <- function(df, var_name) {
df %>%
group_by(across(all_of(var_name))) %>%
summarise(count = n()) %>%
ungroup() %>%
arrange(desc(count))
}
# List of categorical variables to summarize
categorical_vars <- c("a", "res_tour", "Temps_peche_estime.cat2h", "zone.gp",
"age_classe" ,"cat_pro.gp", "poss_bat", "time.day.gp", "nb_sort_an_cat", "dep.mod_peche.chr", "classe_avis_pnm")
# Summarize counts for each categorical variable
summary_list <- lapply(categorical_vars, function(var) count_levels(df.mod.large, var))
# Display summaries
names(summary_list) <- categorical_vars
summary_list
## $a
## # A tibble: 3 × 2
## a count
## <fct> <int>
## 1 2020 100
## 2 2022 82
## 3 2021 70
##
## $res_tour
## # A tibble: 2 × 2
## res_tour count
## <fct> <int>
## 1 resident 196
## 2 non-resident 56
##
## $Temps_peche_estime.cat2h
## # A tibble: 2 × 2
## Temps_peche_estime.cat2h count
## <fct> <int>
## 1 >=2h 228
## 2 <2h 24
##
## $zone.gp
## # A tibble: 4 × 2
## zone.gp count
## <fct> <int>
## 1 Est-Nord Cap 119
## 2 nimp_ou 70
## 3 Agriates_St-Florent 38
## 4 Ouest-Nord Cap 25
##
## $age_classe
## # A tibble: 3 × 2
## age_classe count
## <fct> <int>
## 1 40-59 171
## 2 13-40 44
## 3 60 et plus 37
##
## $cat_pro.gp
## # A tibble: 3 × 2
## cat_pro.gp count
## <fct> <int>
## 1 activite 129
## 2 retraite 96
## 3 sans_emploi-en_arret-etudiant 27
##
## $poss_bat
## # A tibble: 2 × 2
## poss_bat count
## <fct> <int>
## 1 non 134
## 2 oui 118
##
## $time.day.gp
## # A tibble: 3 × 2
## time.day.gp count
## <fct> <int>
## 1 am 129
## 2 nimp_q 92
## 3 pm 31
##
## $nb_sort_an_cat
## # A tibble: 3 × 2
## nb_sort_an_cat count
## <fct> <int>
## 1 Q1 (<=15) 143
## 2 Q3 (>=31) 57
## 3 Q2 (16-30) 52
##
## $dep.mod_peche.chr
## # A tibble: 3 × 2
## dep.mod_peche.chr count
## <fct> <int>
## 1 < 100-500 euros 149
## 2 entre 500-2000 euros 53
## 3 > 2000 euros 50
##
## $classe_avis_pnm
## # A tibble: 3 × 2
## classe_avis_pnm count
## <fct> <int>
## 1 positif 211
## 2 p_avis 39
## 3 negatif 2
filter(df.mod.large, classe_avis_pnm != "negatif") -> df.mod.large
df.mod.large <- droplevels(df.mod.large)
(count_table <- df.mod.large %>%
group_by(a, res_tour, Temps_peche_estime.cat2h, zone.gp,
age_classe ,cat_pro.gp, poss_bat, time.day.gp, nb_sort_an_cat, dep.mod_peche.chr, classe_avis_pnm) %>%
summarise(count = n()) %>%
ungroup())
## `summarise()` has grouped output by 'a', 'res_tour',
## 'Temps_peche_estime.cat2h', 'zone.gp', 'age_classe', 'cat_pro.gp', 'poss_bat',
## 'time.day.gp', 'nb_sort_an_cat', 'dep.mod_peche.chr'. You can override using
## the `.groups` argument.
## # A tibble: 197 × 12
## a res_tour Temps_peche_estime.c…¹ zone.gp age_classe cat_pro.gp poss_bat
## <fct> <fct> <fct> <fct> <fct> <fct> <fct>
## 1 2020 non-resi… <2h Agriat… 40-59 activite non
## 2 2020 non-resi… <2h Agriat… 40-59 activite non
## 3 2020 non-resi… <2h Est-No… 40-59 activite non
## 4 2020 non-resi… >=2h Agriat… 13-40 activite non
## 5 2020 non-resi… >=2h Agriat… 40-59 activite non
## 6 2020 non-resi… >=2h Agriat… 40-59 activite oui
## 7 2020 non-resi… >=2h Agriat… 40-59 retraite oui
## 8 2020 non-resi… >=2h Agriat… 40-59 retraite oui
## 9 2020 non-resi… >=2h Agriat… 40-59 retraite oui
## 10 2020 non-resi… >=2h Est-No… 13-40 activite non
## # ℹ 187 more rows
## # ℹ abbreviated name: ¹Temps_peche_estime.cat2h
## # ℹ 5 more variables: time.day.gp <fct>, nb_sort_an_cat <fct>,
## # dep.mod_peche.chr <fct>, classe_avis_pnm <fct>, count <int>
multinom_model.large <- multinom(mod_peche ~ .
#-poss_bat
, data = df.mod.large)
## # weights: 63 (40 variable)
## initial value 274.653072
## iter 10 value 74.415543
## iter 20 value 60.948216
## iter 30 value 60.329785
## iter 40 value 60.212930
## iter 50 value 60.207057
## iter 60 value 60.206847
## final value 60.206845
## converged
summary(multinom_model.large)
## Call:
## multinom(formula = mod_peche ~ ., data = df.mod.large)
##
## Coefficients:
## (Intercept) a2021 a2022 res_tourresident
## chasse sous-marine -24.299730 -2.3748554 -3.237673 -0.1523195
## peche embarquée -6.071217 0.9482075 -1.187560 -0.4155593
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.8452646 20.887299
## peche embarquée 3.3410974 -2.318376
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 24.7764119 22.2053179 -1.817833
## peche embarquée -0.7220505 -0.4807838 1.968885
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 10.018189 -24.23298
## peche embarquée 5.723163 -1.00971
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine -0.3544662 3.166767
## peche embarquée -0.2296474 6.882713
## time.day.gpnimp_q time.day.gppm nb_sort_an_catQ2 (16-30)
## chasse sous-marine -2.9686197 0.491188 -18.8098907
## peche embarquée -0.3359877 -2.209436 -0.4262691
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 0.6249269 -17.519962
## peche embarquée -3.0587317 3.506792
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.3280822 2.8827650
## peche embarquée 0.7129771 0.8203234
##
## Std. Errors:
## (Intercept) a2021 a2022 res_tourresident
## chasse sous-marine 1.663396 1.721685 2.038851 0.9695762
## peche embarquée 2.075070 1.125790 1.679591 0.9632415
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 1.165796 0.9912214
## peche embarquée 1.239238 0.9802298
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 1.562865 1.236470 0.7446213
## peche embarquée 1.247861 1.326511 1.2177576
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 476.454781 381.1623654
## peche embarquée 2.246717 0.9632374
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine 0.9835731 1.413099
## peche embarquée 1.3540506 1.183415
## time.day.gpnimp_q time.day.gppm nb_sort_an_catQ2 (16-30)
## chasse sous-marine 2.032192 0.8219589 4.874149e-06
## peche embarquée 1.225041 1.7556863 1.144434e+00
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 1.592615 98.129012
## peche embarquée 1.263424 1.741781
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.177825 1.420527
## peche embarquée 1.011449 1.334318
##
## Residual Deviance: 120.4137
## AIC: 200.4137
#interpret the coefficients in terms of odds ratios
exp(coef(multinom_model.large))
## (Intercept) a2021 a2022 res_tourresident
## chasse sous-marine 2.797444e-11 0.09302794 0.03925512 0.8587139
## peche embarquée 2.308362e-03 2.58107882 0.30496440 0.6599711
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 2.328594 1.178254e+09
## peche embarquée 28.250113 9.843330e-02
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 5.757832e+10 4.401969e+09 0.1623772
## peche embarquée 4.857552e-01 6.182986e-01 7.1626855
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 22430.7640 2.990535e-11
## peche embarquée 305.8708 3.643245e-01
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine 0.7015478 23.73064
## peche embarquée 0.7948138 975.26909
## time.day.gpnimp_q time.day.gppm nb_sort_an_catQ2 (16-30)
## chasse sous-marine 0.05137417 1.6342566 6.775920e-09
## peche embarquée 0.71463186 0.1097626 6.529406e-01
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 1.8681094 2.461371e-08
## peche embarquée 0.0469472 3.334115e+01
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 3.773799 17.863597
## peche embarquée 2.040056 2.271234
(multinom.tbl.large <- tidy(multinom_model.large, conf.int = TRUE))
## # A tibble: 40 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-m… (Int… -24.3 1.66 -14.6 2.48e-48 -27.6 -21.0
## 2 chasse sous-m… a2021 -2.37 1.72 -1.38 1.68e- 1 -5.75 1.00
## 3 chasse sous-m… a2022 -3.24 2.04 -1.59 1.12e- 1 -7.23 0.758
## 4 chasse sous-m… res_… -0.152 0.970 -0.157 8.75e- 1 -2.05 1.75
## 5 chasse sous-m… Temp… 0.845 1.17 0.725 4.68e- 1 -1.44 3.13
## 6 chasse sous-m… zone… 20.9 0.991 21.1 1.43e-98 18.9 22.8
## 7 chasse sous-m… zone… 24.8 1.56 15.9 1.34e-56 21.7 27.8
## 8 chasse sous-m… zone… 22.2 1.24 18.0 4.11e-72 19.8 24.6
## 9 chasse sous-m… age_… -1.82 0.745 -2.44 1.46e- 2 -3.28 -0.358
## 10 chasse sous-m… age_… 10.0 476. 0.0210 9.83e- 1 -924. 944.
## # ℹ 30 more rows
(multinom.tbl.large.sign <- filter(multinom.tbl.large, p.value < 0.05))
## # A tibble: 15 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-m… (Int… -24.3 1.66e+0 -1.46e1 2.48e-48 -27.6 -21.0
## 2 chasse sous-m… zone… 20.9 9.91e-1 2.11e1 1.43e-98 18.9 22.8
## 3 chasse sous-m… zone… 24.8 1.56e+0 1.59e1 1.34e-56 21.7 27.8
## 4 chasse sous-m… zone… 22.2 1.24e+0 1.80e1 4.11e-72 19.8 24.6
## 5 chasse sous-m… age_… -1.82 7.45e-1 -2.44e0 1.46e- 2 -3.28 -0.358
## 6 chasse sous-m… poss… 3.17 1.41e+0 2.24e0 2.50e- 2 0.397 5.94
## 7 chasse sous-m… nb_s… -18.8 4.87e-6 -3.86e6 0 -18.8 -18.8
## 8 chasse sous-m… clas… 2.88 1.42e+0 2.03e0 4.24e- 2 0.0986 5.67
## 9 peche embarqu… (Int… -6.07 2.08e+0 -2.93e0 3.44e- 3 -10.1 -2.00
## 10 peche embarqu… Temp… 3.34 1.24e+0 2.70e0 7.02e- 3 0.912 5.77
## 11 peche embarqu… zone… -2.32 9.80e-1 -2.37e0 1.80e- 2 -4.24 -0.397
## 12 peche embarqu… age_… 5.72 2.25e+0 2.55e0 1.09e- 2 1.32 10.1
## 13 peche embarqu… poss… 6.88 1.18e+0 5.82e0 6.03e- 9 4.56 9.20
## 14 peche embarqu… nb_s… -3.06 1.26e+0 -2.42e0 1.55e- 2 -5.53 -0.582
## 15 peche embarqu… dep.… 3.51 1.74e+0 2.01e0 4.41e- 2 0.0930 6.92
#Messages d'avis :
#1: Dans sqrt(diag(vc)) : Production de NaN
#2: Dans sqrt(diag(vcov(object))) : Production de NaN
# All of the observations are zero for some combination of factors. Thus any coefficient that involves a comparison with this state will have a parameter value of large magnitude (i.e. abs(beta) >> 1); it should theoretically be infinite, but is usually somewhere between 10 and 30 (depending on where the numerical methods give up). These coefficients will either have ridiculously large standard errors and (Wald) confidence intervals, or (as in your case) NaN values (https://stackoverflow.com/questions/67338560/zeroinfl-model-warning-message-in-sqrtdiagobjectvcov-nans-produced)
#https://www.youtube.com/@bkrai
#https://www.youtube.com/watch?v=S2rZp4L_nXo
#https://www.youtube.com/watch?v=oxRy2DMrOF4
#https://www.youtube.com/watch?v=11VY8CmNVDQ
#https://www.youtube.com/watch?v=POyTaeneHJY
#2-tailed Z-test (idem result than with above tidy function on model)
z <- summary(multinom_model.large)$coefficient/summary(multinom_model.large)$standard.errors
(p <- (1 - pnorm(abs(z), 0, 1)) * 2)
## (Intercept) a2021 a2022 res_tourresident
## chasse sous-marine 0.000000000 0.1677780 0.1122889 0.8751668
## peche embarquée 0.003435836 0.3996425 0.4795334 0.6661648
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.468418988 0.00000000
## peche embarquée 0.007015882 0.01802348
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 0.0000000 0.0000000 0.01463507
## peche embarquée 0.5628384 0.7170215 0.10591888
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 0.98322450 0.9493074
## peche embarquée 0.01085461 0.2945250
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine 0.7185583 2.502547e-02
## peche embarquée 0.8653245 6.028083e-09
## time.day.gpnimp_q time.day.gppm nb_sort_an_catQ2 (16-30)
## chasse sous-marine 0.1440712 0.5501187 0.0000000
## peche embarquée 0.7838797 0.2082306 0.7095417
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 0.69476967 0.85829884
## peche embarquée 0.01547852 0.04407916
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 0.2595009 0.0424213
## peche embarquée 0.4808681 0.5386944
multinom_model.large.sign <- multinom(mod_peche ~ . -a -res_tour -cat_pro.gp -time.day.gp
#- poss_bat -res_tour -classe_avis_pnm -Temps_peche_estime.cat2h -cat_pro.gp
, data = df.mod.large)
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 78.710794
## iter 20 value 72.087606
## iter 30 value 71.632758
## iter 40 value 71.613465
## final value 71.613298
## converged
summary(multinom_model.large.sign)
## Warning in sqrt(diag(vc)): Production de NaN
## Call:
## multinom(formula = mod_peche ~ . - a - res_tour - cat_pro.gp -
## time.day.gp, data = df.mod.large)
##
## Coefficients:
## (Intercept) Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine -30.72813 1.268155 26.771149
## peche embarquée -6.73359 3.136043 -2.314848
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 27.75157 26.8375087 -2.474072
## peche embarquée -1.19195 -0.9030687 1.378754
## age_classe60 et plus poss_batoui nb_sort_an_catQ2 (16-30)
## chasse sous-marine -15.855019 2.206396 -26.3185692
## peche embarquée 3.289682 6.767189 -0.1095195
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine -1.651513 -30.002333
## peche embarquée -3.059482 3.420796
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.650145 2.828466
## peche embarquée 1.192845 1.503685
##
## Std. Errors:
## (Intercept) Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 1.320733 1.129788 0.6769129
## peche embarquée 1.876292 1.126920 0.9081880
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 0.8567323 0.9856822 0.6722375
## peche embarquée 1.0594817 1.1845970 1.0024281
## age_classe60 et plus poss_batoui nb_sort_an_catQ2 (16-30)
## chasse sous-marine 1067.572443 1.136282 NaN
## peche embarquée 1.641074 1.100015 0.9591665
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 1.024634 9.074735e-08
## peche embarquée 1.095705 1.476633e+00
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.1081408 1.341443
## peche embarquée 0.8967854 1.232224
##
## Residual Deviance: 143.2266
## AIC: 195.2266
z <- summary(multinom_model.large.sign)$coefficient/summary(multinom_model.large.sign)$standard.errors
## Warning in sqrt(diag(vc)): Production de NaN
## Warning in sqrt(diag(vc)): Production de NaN
(p <- (1 - pnorm(abs(z), 0, 1)) * 2)
## (Intercept) Temps_peche_estime.cat2h>=2h
## chasse sous-marine 0.0000000000 0.261661918
## peche embarquée 0.0003322344 0.005388482
## zone.gpEst-Nord Cap zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 0.00000000 0.0000000 0.0000000
## peche embarquée 0.01080743 0.2605759 0.4458556
## age_classe40-59 age_classe60 et plus poss_batoui
## chasse sous-marine 0.0002329101 0.98815068 5.216524e-02
## peche embarquée 0.1690031634 0.04500678 7.655694e-10
## nb_sort_an_catQ2 (16-30) nb_sort_an_catQ3 (>=31)
## chasse sous-marine NaN 0.107003639
## peche embarquée 0.9090936 0.005234296
## dep.mod_peche.chr> 2000 euros
## chasse sous-marine 0.00000000
## peche embarquée 0.02052452
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 0.1364581 0.03498557
## peche embarquée 0.1834739 0.22235037
table(df.mod.large$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 114 16 120
# Data partition and modeling
set.seed(222)
ind <- sample(2, nrow(df.mod.large), replace = T, prob = c(.6,.4))
training <- df.mod.large[ind==1,]
testing <- df.mod.large[ind==2,]
table(training$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 63 9 72
table(testing$mod_peche)
##
## peche du bord chasse sous-marine peche embarquée
## 51 7 48
multinom_model.training <- multinom(mod_peche ~ . -a -res_tour -cat_pro.gp -time.day.gp
#- poss_bat -res_tour -classe_avis_pnm -Temps_peche_estime.cat2h -cat_pro.gp
, data = training)
## # weights: 42 (26 variable)
## initial value 158.200170
## iter 10 value 34.869587
## iter 20 value 28.288076
## iter 30 value 28.054306
## iter 40 value 27.996912
## iter 50 value 27.972608
## iter 60 value 27.969294
## iter 70 value 27.969040
## iter 80 value 27.968314
## iter 90 value 27.967935
## iter 100 value 27.967735
## final value 27.967735
## stopped after 100 iterations
# Confusion matrix and misclassification error - training data
(p <- predict(multinom_model.training, training))
## [1] peche du bord peche du bord peche embarquée
## [4] peche du bord peche embarquée peche du bord
## [7] peche du bord peche du bord peche du bord
## [10] chasse sous-marine peche du bord peche embarquée
## [13] peche embarquée peche embarquée peche du bord
## [16] peche embarquée peche embarquée peche embarquée
## [19] peche du bord peche du bord peche du bord
## [22] peche du bord peche du bord peche du bord
## [25] peche du bord peche du bord peche embarquée
## [28] peche du bord peche du bord peche du bord
## [31] peche du bord peche du bord peche du bord
## [34] peche du bord peche du bord peche du bord
## [37] peche du bord peche du bord peche du bord
## [40] peche du bord chasse sous-marine peche du bord
## [43] peche du bord peche du bord peche du bord
## [46] peche du bord peche du bord chasse sous-marine
## [49] peche du bord peche du bord chasse sous-marine
## [52] peche du bord peche du bord peche embarquée
## [55] peche du bord peche du bord peche embarquée
## [58] peche embarquée peche embarquée peche embarquée
## [61] peche embarquée peche embarquée peche embarquée
## [64] peche embarquée peche embarquée peche embarquée
## [67] peche embarquée peche embarquée peche embarquée
## [70] peche embarquée peche embarquée peche embarquée
## [73] peche embarquée peche embarquée peche embarquée
## [76] peche embarquée peche embarquée peche embarquée
## [79] peche embarquée peche du bord peche du bord
## [82] peche embarquée peche embarquée peche du bord
## [85] peche du bord peche du bord peche du bord
## [88] peche embarquée peche embarquée peche embarquée
## [91] peche du bord peche du bord peche du bord
## [94] peche du bord peche du bord peche embarquée
## [97] peche embarquée peche du bord peche du bord
## [100] peche du bord peche embarquée peche embarquée
## [103] peche embarquée peche embarquée peche embarquée
## [106] peche embarquée peche du bord peche embarquée
## [109] peche embarquée peche embarquée peche embarquée
## [112] peche embarquée peche du bord peche du bord
## [115] peche du bord peche du bord peche du bord
## [118] peche du bord peche du bord peche du bord
## [121] peche du bord peche embarquée peche du bord
## [124] peche embarquée chasse sous-marine peche embarquée
## [127] peche embarquée peche embarquée peche embarquée
## [130] peche embarquée peche embarquée peche embarquée
## [133] peche embarquée peche embarquée peche embarquée
## [136] peche embarquée peche embarquée peche embarquée
## [139] peche embarquée peche embarquée peche embarquée
## [142] peche embarquée peche embarquée peche embarquée
## Levels: peche du bord chasse sous-marine peche embarquée
(tab <- table(p, training$mod_peche))
##
## p peche du bord chasse sous-marine peche embarquée
## peche du bord 61 4 2
## chasse sous-marine 2 3 0
## peche embarquée 0 2 70
1 - sum(diag(tab))/sum(tab) # misclassification
## [1] 0.06944444
# Confusion matrix and misclassification error - testing data
(p1 <- predict(multinom_model.training, testing))
## [1] peche du bord peche embarquée peche embarquée
## [4] peche du bord chasse sous-marine peche du bord
## [7] peche embarquée peche embarquée peche du bord
## [10] peche du bord peche embarquée chasse sous-marine
## [13] peche du bord peche du bord peche du bord
## [16] peche du bord peche du bord peche du bord
## [19] peche embarquée peche du bord peche du bord
## [22] chasse sous-marine peche du bord peche du bord
## [25] peche du bord peche du bord peche du bord
## [28] peche du bord chasse sous-marine chasse sous-marine
## [31] peche du bord peche du bord peche du bord
## [34] peche du bord peche du bord peche du bord
## [37] peche du bord peche du bord peche du bord
## [40] peche du bord peche embarquée chasse sous-marine
## [43] peche embarquée peche embarquée peche du bord
## [46] chasse sous-marine peche embarquée peche du bord
## [49] peche du bord peche du bord peche embarquée
## [52] peche du bord peche embarquée peche embarquée
## [55] peche embarquée peche embarquée peche embarquée
## [58] peche embarquée peche embarquée peche embarquée
## [61] peche embarquée peche embarquée peche du bord
## [64] peche embarquée peche du bord peche du bord
## [67] peche embarquée peche embarquée peche embarquée
## [70] peche du bord peche du bord peche embarquée
## [73] peche embarquée peche du bord peche du bord
## [76] peche embarquée peche embarquée peche embarquée
## [79] peche embarquée peche embarquée peche du bord
## [82] peche du bord peche embarquée peche du bord
## [85] peche du bord peche du bord peche du bord
## [88] peche du bord peche du bord peche du bord
## [91] peche du bord peche du bord peche du bord
## [94] peche embarquée peche embarquée peche embarquée
## [97] peche embarquée peche embarquée peche embarquée
## [100] peche embarquée peche embarquée peche embarquée
## [103] peche embarquée peche embarquée peche embarquée
## [106] peche embarquée
## Levels: peche du bord chasse sous-marine peche embarquée
(tab1 <- table(p1, testing$mod_peche))
##
## p1 peche du bord chasse sous-marine peche embarquée
## peche du bord 46 3 4
## chasse sous-marine 3 3 1
## peche embarquée 2 1 43
1 - sum(diag(tab1))/sum(tab1) # misclassification
## [1] 0.1320755
tab/colSums(tab)
##
## p peche du bord chasse sous-marine peche embarquée
## peche du bord 0.96825397 0.06349206 0.03174603
## chasse sous-marine 0.22222222 0.33333333 0.00000000
## peche embarquée 0.00000000 0.02777778 0.97222222
tab1/colSums(tab1)
##
## p1 peche du bord chasse sous-marine peche embarquée
## peche du bord 0.90196078 0.05882353 0.07843137
## chasse sous-marine 0.42857143 0.42857143 0.14285714
## peche embarquée 0.04166667 0.02083333 0.89583333
# obviously I now have enough variable to model chasse sous-marine class !!
# Check assumptions for multinomial logistic regression:
#Assumption 1: Independence of observations.
#Assumption 2: Independence of Irrelevant Alternatives (IIA); i.e. Categories of the outcome variable must be mutually exclusive and exhaustive.
#Use the Hausman-McFadden test to check the IIA assumption. However, this test is not directly available in R, so we'll use an approximation.
# IIA assumption check
iia_test <- function(model, data, formula) {
reduced_model <- update(model, . ~ . - predictor1) # Example, modify as needed
model_ll <- logLik(model)
reduced_model_ll <- logLik(reduced_model)
chi_square <- 2 * (model_ll - reduced_model_ll)
p_value <- pchisq(chi_square, df = length(coef(model)) - length(coef(reduced_model)), lower.tail = FALSE)
return(p_value)
}
iia_result <- iia_test(model = multinom_model.large, data = df.mod.large, mod_peche ~ a + res_tour + Temps_peche_estime.cat2h + zone.gp
+ age_classe + cat_pro.gp + poss_bat + time.day.gp + nb_sort_an_cat + dep.mod_peche.chr + classe_avis_pnm)
## # weights: 63 (40 variable)
## initial value 274.653072
## iter 10 value 74.415543
## iter 20 value 60.948216
## iter 30 value 60.329785
## iter 40 value 60.212930
## iter 50 value 60.207057
## iter 60 value 60.206847
## final value 60.206845
## converged
print(iia_result)
## 'log Lik.' 1 (df=40)
#Assumption 3: No Multicollinearity between independent variables.
#Check multicollinearity using the Variance Inflation Factor (VIF).
vif_results <- vif(multinom_model.large)
## Warning in vif.default(multinom_model.large): No intercept: vifs may not be
## sensible.
print(vif_results)
## GVIF Df GVIF^(1/(2*Df))
## a -7.800874e+13 2 NaN
## res_tour -4.494489e+09 1 NaN
## Temps_peche_estime.cat2h -2.195225e+11 1 NaN
## zone.gp -2.582040e+29 3 NaN
## age_classe -1.875548e+22 2 NaN
## cat_pro.gp -1.058300e+27 2 NaN
## poss_bat 2.071189e+11 1 455103.155
## time.day.gp 9.601547e+12 2 1760.294
## nb_sort_an_cat 2.696061e+16 2 12813.933
## dep.mod_peche.chr 7.039491e+26 2 5150926.113
## classe_avis_pnm 4.044528e+10 1 201110.124
#Warning message
#glm.fit: algorithm did not converge
#This warning often occurs when you attempt to fit a logistic regression model in R and you experience perfect separation – that is, a predictor variable is able to perfectly separate the response variable into 0’s and 1’s. (https://www.statology.org/glm-fit-algorithm-did-not-converge/)
labels = rownames(coefficients(multinom_model.large))
ref = setdiff(multinom_model.large$lab,labels)
t(sapply(labels,function(i){
dat = df.mod.large
dat$mod_peche = as.numeric(dat$mod_peche == i)
vif.i <<- vif(glm(mod_peche ~ .,data=dat,family="binomial"))
}))
## Warning: glm.fit: des probabilités ont été ajustées numériquement à 0 ou 1
## [,1] [,2] [,3] [,4] [,5] [,6]
## chasse sous-marine 7.397834 1.393769 1.128580 9.989664 1.916456 2.078508
## peche embarquée 6.270478 1.512973 1.597978 2.705570 4.429303 2.369068
## [,7] [,8] [,9] [,10] [,11] [,12] [,13]
## chasse sous-marine 2.102295 4.587100 3.200762 2.088174 1.147449 2 1
## peche embarquée 3.042183 4.471479 3.270830 2.211451 1.339612 2 1
## [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
## chasse sous-marine 1 3 2 2 1 2 2 2 1
## peche embarquée 1 3 2 2 1 2 2 2 1
## [,23] [,24] [,25] [,26] [,27] [,28]
## chasse sous-marine 1.649211 1.18058 1.062346 1.467546 1.176589 1.200709
## peche embarquée 1.582432 1.23003 1.264111 1.180438 1.450721 1.240636
## [,29] [,30] [,31] [,32] [,33]
## chasse sous-marine 1.449929 1.463472 1.337560 1.202103 1.071191
## peche embarquée 1.744185 1.454162 1.344821 1.219465 1.157416
# check if vif still to high in the reduced model
labels = rownames(coefficients(multinom_model.large.sign))
ref = setdiff(multinom_model.large.sign$lab,labels)
t(sapply(labels,function(i){
dat = df.mod.large
dat$mod_peche = as.numeric(dat$mod_peche == i)
vif.i <<- vif(glm(mod_peche ~ . -a -res_tour -cat_pro.gp -time.day.gp
#- poss_bat -res_tour -classe_avis_pnm -Temps_peche_estime.cat2h -cat_pro.gp
, data=dat,family="binomial"))
}))
## Warning: glm.fit: des probabilités ont été ajustées numériquement à 0 ou 1
## [,1] [,2] [,3] [,4] [,5] [,6]
## chasse sous-marine 1.101483 1.660285 1.127855 1.613138 1.306382 1.895336
## peche embarquée 1.418268 1.782910 2.035911 2.469022 2.259681 2.108323
## [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15]
## chasse sous-marine 1.106832 1 3 2 1 2 2 1 1.049516
## peche embarquée 1.235058 1 3 2 1 2 2 1 1.190911
## [,16] [,17] [,18] [,19] [,20] [,21]
## chasse sous-marine 1.088171 1.030536 1.270094 1.069098 1.173334 1.052061
## peche embarquée 1.101171 1.194510 1.571312 1.226060 1.204992 1.111332
#Assumption 4: Linearity in the logit (for continuous variables); i.e. Linear relationship between continuous variables and the logit transformation of the outcome variable.
#Assumption 5: No outliers or highly influential points.
#Also, absolute minimum of cases or multinomial logistic regression indicates a minimum of 10 cases per independent variable.
# stepwize regression for Multinomial Logistic Regression Model. (http://www.sthda.com/english/articles/36-classification-methods-essentials/150-stepwise-logistic-regression-essentials-in-r/)
# the null model contains only the intercept; the full model contains all predictors
(null_model <- multinom(mod_peche ~ 1, data = df.mod.large))
## # weights: 6 (2 variable)
## initial value 274.653072
## final value 221.578178
## converged
## Call:
## multinom(formula = mod_peche ~ 1, data = df.mod.large)
##
## Coefficients:
## (Intercept)
## chasse sous-marine -1.96360949
## peche embarquée 0.05129325
##
## Residual Deviance: 443.1564
## AIC: 447.1564
(multinom_model.large)
## Call:
## multinom(formula = mod_peche ~ ., data = df.mod.large)
##
## Coefficients:
## (Intercept) a2021 a2022 res_tourresident
## chasse sous-marine -24.299730 -2.3748554 -3.237673 -0.1523195
## peche embarquée -6.071217 0.9482075 -1.187560 -0.4155593
## Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 0.8452646 20.887299
## peche embarquée 3.3410974 -2.318376
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 24.7764119 22.2053179 -1.817833
## peche embarquée -0.7220505 -0.4807838 1.968885
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 10.018189 -24.23298
## peche embarquée 5.723163 -1.00971
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine -0.3544662 3.166767
## peche embarquée -0.2296474 6.882713
## time.day.gpnimp_q time.day.gppm nb_sort_an_catQ2 (16-30)
## chasse sous-marine -2.9686197 0.491188 -18.8098907
## peche embarquée -0.3359877 -2.209436 -0.4262691
## nb_sort_an_catQ3 (>=31) dep.mod_peche.chr> 2000 euros
## chasse sous-marine 0.6249269 -17.519962
## peche embarquée -3.0587317 3.506792
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.3280822 2.8827650
## peche embarquée 0.7129771 0.8203234
##
## Residual Deviance: 120.4137
## AIC: 200.4137
# use the stepAIC function from the MASS package, which performs both forward and backward stepwise selection based on AIC (Akaike Information Criterion)
stepwise_model.forward <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.large), direction = "both")
## Start: AIC=447.16
## mod_peche ~ 1
##
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 197.057558
## final value 197.053042
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## final value 221.301862
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## final value 219.966908
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 197.063658
## iter 20 value 196.477813
## iter 30 value 196.476702
## final value 196.472095
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 202.910938
## iter 20 value 202.676515
## final value 202.663441
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 208.878238
## iter 20 value 208.220177
## final value 208.197007
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 203.745306
## final value 203.742661
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 210.741239
## iter 20 value 210.308334
## final value 210.282872
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 167.988810
## iter 20 value 167.362387
## final value 167.286025
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 218.202664
## final value 218.202659
## converged
## Df AIC
## + poss_bat 2 224.55
## + dep.mod_peche.chr 4 346.57
## + a 4 406.11
## + zone.gp 6 408.94
## + age_classe 4 417.33
## + time.day.gp 4 419.49
## + cat_pro.gp 4 428.39
## + nb_sort_an_cat 4 432.57
## + classe_avis_pnm 2 444.41
## <none> 447.16
## + Temps_peche_estime.cat2h 2 447.93
## + res_tour 2 450.60
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
##
## Step: AIC=224.55
## mod_peche ~ poss_bat
##
## # weights: 6 (2 variable)
## initial value 274.653072
## final value 221.578178
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.561792
## final value 106.510950
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 108.268768
## final value 108.258547
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 105.778202
## final value 105.773207
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 103.245538
## iter 20 value 102.549576
## final value 102.545096
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 101.569368
## iter 20 value 100.309789
## iter 30 value 100.292327
## final value 100.291852
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 102.388445
## final value 102.349817
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.536089
## iter 20 value 101.389387
## iter 30 value 101.316024
## final value 101.314815
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 103.443206
## iter 20 value 102.777542
## iter 30 value 102.765320
## final value 102.764870
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 105.716608
## final value 105.705357
## converged
## Df AIC
## + age_classe 4 216.29
## + cat_pro.gp 4 216.58
## + nb_sort_an_cat 4 218.63
## + time.day.gp 4 220.70
## + dep.mod_peche.chr 4 221.53
## + classe_avis_pnm 2 223.41
## + Temps_peche_estime.cat2h 2 223.55
## <none> 224.55
## + zone.gp 6 225.09
## + res_tour 2 228.52
## + a 4 229.02
## - poss_bat 2 447.16
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
##
## Step: AIC=216.29
## mod_peche ~ poss_bat + age_classe
##
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 202.910938
## iter 20 value 202.676515
## final value 202.663441
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 96.517288
## iter 20 value 95.967321
## iter 30 value 95.955771
## final value 95.955761
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 100.428861
## iter 20 value 100.063801
## iter 30 value 100.057831
## iter 40 value 100.055700
## final value 100.055682
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 98.066402
## iter 20 value 97.411184
## iter 30 value 97.395156
## iter 40 value 97.391430
## final value 97.391341
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 95.580854
## iter 20 value 94.121933
## iter 30 value 94.095631
## final value 94.095620
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 97.088787
## iter 20 value 96.115318
## iter 30 value 96.090899
## iter 40 value 96.090307
## final value 96.089942
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 94.796583
## iter 20 value 94.225747
## iter 30 value 94.212187
## final value 94.212171
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.399464
## iter 20 value 94.335888
## iter 30 value 94.324995
## final value 94.324979
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 97.440295
## iter 20 value 97.106838
## iter 30 value 97.101498
## iter 40 value 97.099352
## final value 97.099317
## converged
## Df AIC
## + nb_sort_an_cat 4 208.61
## + time.day.gp 4 212.42
## + dep.mod_peche.chr 4 212.65
## + classe_avis_pnm 2 214.20
## + Temps_peche_estime.cat2h 2 214.78
## + a 4 215.91
## + cat_pro.gp 4 216.18
## + zone.gp 6 216.19
## <none> 216.29
## + res_tour 2 220.11
## - age_classe 4 224.55
## - poss_bat 2 417.33
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
##
## Step: AIC=208.61
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat
##
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 194.992567
## iter 20 value 192.277323
## final value 192.272811
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.536089
## iter 20 value 101.389387
## iter 30 value 101.316024
## final value 101.314815
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.511257
## iter 20 value 90.075201
## iter 30 value 90.042175
## final value 90.041999
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 93.651925
## iter 20 value 92.295985
## iter 30 value 92.240683
## final value 92.240647
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 91.658938
## iter 20 value 89.670365
## iter 30 value 89.555570
## iter 40 value 89.555488
## iter 50 value 89.554772
## final value 89.554690
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 89.952261
## iter 20 value 86.857659
## iter 30 value 86.788393
## final value 86.787513
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 89.755125
## iter 20 value 87.584774
## iter 30 value 87.506661
## final value 87.506108
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.214458
## iter 20 value 88.611164
## iter 30 value 88.559801
## iter 40 value 88.559550
## iter 40 value 88.559550
## iter 40 value 88.559550
## final value 88.559550
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 90.941388
## iter 20 value 89.654820
## iter 30 value 89.587298
## final value 89.587274
## converged
## Df AIC
## + dep.mod_peche.chr 4 200.62
## + cat_pro.gp 4 207.01
## + Temps_peche_estime.cat2h 2 207.11
## + classe_avis_pnm 2 207.17
## <none> 208.61
## + time.day.gp 4 209.12
## + zone.gp 6 209.58
## + a 4 212.08
## + res_tour 2 212.48
## - nb_sort_an_cat 4 216.29
## - age_classe 4 218.63
## - poss_bat 2 404.55
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
##
## Step: AIC=200.62
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr
##
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 147.259443
## iter 20 value 143.573206
## iter 30 value 143.548107
## final value 143.548085
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.874589
## iter 20 value 94.787853
## iter 30 value 94.733408
## iter 40 value 94.729991
## iter 50 value 94.729749
## final value 94.729729
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.399464
## iter 20 value 94.335888
## iter 30 value 94.324995
## final value 94.324979
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 86.837732
## iter 20 value 82.479256
## iter 30 value 82.387856
## iter 40 value 82.387328
## final value 82.387325
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 86.739004
## iter 20 value 84.434189
## iter 30 value 84.300764
## final value 84.299630
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 86.217292
## iter 20 value 79.764922
## iter 30 value 79.431740
## iter 40 value 79.427352
## final value 79.427342
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.429772
## iter 20 value 80.127862
## iter 30 value 80.028891
## iter 40 value 80.027972
## final value 80.027968
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 83.779798
## iter 20 value 80.366096
## iter 30 value 80.240340
## iter 40 value 80.239380
## final value 80.239374
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 85.433497
## iter 20 value 81.656495
## iter 30 value 81.457614
## final value 81.454826
## converged
## Df AIC
## + Temps_peche_estime.cat2h 2 198.88
## + classe_avis_pnm 2 198.91
## + cat_pro.gp 4 200.06
## + time.day.gp 4 200.48
## <none> 200.62
## + zone.gp 6 202.85
## + res_tour 2 204.60
## + a 4 204.78
## - dep.mod_peche.chr 4 208.61
## - nb_sort_an_cat 4 212.65
## - age_classe 4 213.46
## - poss_bat 2 315.10
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
##
## Step: AIC=198.88
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h
##
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 144.786436
## iter 20 value 142.865929
## iter 30 value 142.840298
## final value 142.840221
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 94.077343
## iter 20 value 93.085401
## iter 30 value 93.057419
## final value 93.057418
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 93.346994
## iter 20 value 91.919583
## iter 30 value 91.842398
## final value 91.842375
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 91.658938
## iter 20 value 89.670365
## iter 30 value 89.555570
## iter 40 value 89.555488
## iter 50 value 89.554772
## final value 89.554690
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 85.455932
## iter 20 value 79.975636
## iter 30 value 79.674216
## iter 40 value 79.669654
## final value 79.669622
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 90.305779
## iter 20 value 81.711648
## iter 30 value 81.424315
## iter 40 value 81.421155
## final value 81.421139
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 81.679078
## iter 20 value 75.845360
## iter 30 value 75.413375
## iter 40 value 75.403995
## final value 75.403967
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.825470
## iter 20 value 77.307926
## iter 30 value 76.853376
## iter 40 value 76.848188
## final value 76.848176
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.124585
## iter 20 value 77.381349
## iter 30 value 77.165242
## iter 40 value 77.159733
## final value 77.159711
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
## Df AIC
## + classe_avis_pnm 2 196.51
## + cat_pro.gp 4 197.70
## + time.day.gp 4 198.32
## + zone.gp 6 198.81
## <none> 198.88
## - Temps_peche_estime.cat2h 2 200.62
## + res_tour 2 202.84
## + a 4 203.34
## - dep.mod_peche.chr 4 207.11
## - nb_sort_an_cat 4 211.68
## - age_classe 4 214.11
## - poss_bat 2 317.68
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
##
## Step: AIC=196.51
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm
##
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 140.868043
## iter 20 value 139.559698
## iter 30 value 139.528212
## final value 139.528073
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.895481
## iter 20 value 90.162318
## iter 30 value 90.076490
## final value 90.075792
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 89.753479
## iter 20 value 88.605408
## iter 30 value 88.530092
## iter 40 value 88.529029
## final value 88.529025
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 87.272451
## iter 20 value 86.550868
## iter 30 value 86.486138
## final value 86.485329
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 85.433497
## iter 20 value 81.656495
## iter 30 value 81.457614
## final value 81.454826
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 80.992206
## iter 20 value 77.072663
## iter 30 value 76.834111
## iter 40 value 76.830467
## final value 76.830408
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 79.932898
## iter 20 value 78.381867
## iter 30 value 78.215932
## iter 40 value 78.197785
## final value 78.197662
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 78.710794
## iter 20 value 72.087606
## iter 30 value 71.632758
## iter 40 value 71.613465
## final value 71.613298
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 77.940965
## iter 20 value 74.113450
## iter 30 value 73.877129
## iter 40 value 73.874320
## final value 73.874260
## converged
## Df AIC
## + cat_pro.gp 4 194.74
## + zone.gp 6 195.23
## + time.day.gp 4 195.75
## <none> 196.51
## - classe_avis_pnm 2 198.88
## - Temps_peche_estime.cat2h 2 198.91
## + res_tour 2 200.40
## + a 4 201.66
## - dep.mod_peche.chr 4 204.97
## - nb_sort_an_cat 4 209.06
## - age_classe 4 212.15
## - poss_bat 2 315.06
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
##
## Step: AIC=194.74
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm + cat_pro.gp
##
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 136.257189
## iter 20 value 134.021670
## iter 30 value 133.886223
## iter 40 value 133.885300
## final value 133.885297
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 84.817178
## iter 20 value 81.013507
## iter 30 value 80.694870
## iter 40 value 80.689948
## final value 80.689927
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 98.992778
## iter 20 value 84.309239
## iter 30 value 84.169007
## iter 40 value 84.141697
## final value 84.141370
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 84.671483
## iter 20 value 81.247938
## iter 30 value 81.046946
## iter 40 value 81.021514
## final value 81.021437
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 85.118669
## iter 20 value 77.334869
## iter 30 value 76.912665
## iter 40 value 76.907503
## final value 76.907491
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.825470
## iter 20 value 77.307926
## iter 30 value 76.853376
## iter 40 value 76.848188
## final value 76.848176
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 78.078561
## iter 20 value 72.012469
## iter 30 value 71.690963
## iter 40 value 71.670319
## final value 71.669418
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.921538
## iter 20 value 73.671272
## iter 30 value 73.276382
## iter 40 value 73.269860
## final value 73.269800
## converged
## # weights: 48 (30 variable)
## initial value 274.653072
## iter 10 value 73.959423
## iter 20 value 67.820214
## iter 30 value 67.117798
## iter 40 value 67.097084
## iter 50 value 67.096887
## iter 50 value 67.096887
## iter 50 value 67.096887
## final value 67.096887
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 79.788562
## iter 20 value 69.750226
## iter 30 value 69.278154
## iter 40 value 69.246797
## iter 50 value 69.245898
## final value 69.245891
## converged
## Df AIC
## + zone.gp 6 194.19
## + time.day.gp 4 194.49
## <none> 194.74
## - cat_pro.gp 4 196.51
## - classe_avis_pnm 2 197.70
## - Temps_peche_estime.cat2h 2 197.81
## + res_tour 2 198.54
## + a 4 199.34
## - age_classe 4 201.38
## - dep.mod_peche.chr 4 202.04
## - nb_sort_an_cat 4 208.28
## - poss_bat 2 311.77
## # weights: 48 (30 variable)
## initial value 274.653072
## iter 10 value 73.959423
## iter 20 value 67.820214
## iter 30 value 67.117798
## iter 40 value 67.097084
## iter 50 value 67.096887
## iter 50 value 67.096887
## iter 50 value 67.096887
## final value 67.096887
## converged
##
## Step: AIC=194.19
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm + cat_pro.gp +
## zone.gp
##
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 128.617357
## iter 20 value 124.715722
## iter 30 value 123.647404
## iter 40 value 123.629623
## final value 123.629577
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.655015
## iter 20 value 74.841123
## iter 30 value 74.342046
## iter 40 value 74.333337
## final value 74.333275
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 83.410741
## iter 20 value 77.307366
## iter 30 value 76.879191
## iter 40 value 76.865496
## final value 76.865437
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.456091
## iter 20 value 74.990185
## iter 30 value 74.581305
## iter 40 value 74.566817
## final value 74.566730
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 77.541715
## iter 20 value 71.998764
## iter 30 value 71.551022
## iter 40 value 71.542406
## final value 71.542369
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 79.662192
## iter 20 value 71.597245
## iter 30 value 71.048090
## iter 40 value 71.036451
## final value 71.036418
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 78.710794
## iter 20 value 72.087606
## iter 30 value 71.632758
## iter 40 value 71.613465
## final value 71.613298
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
## # weights: 54 (34 variable)
## initial value 274.653072
## iter 10 value 74.508734
## iter 20 value 64.493390
## iter 30 value 63.816995
## iter 40 value 63.716597
## iter 50 value 63.715659
## final value 63.715644
## converged
## # weights: 51 (32 variable)
## initial value 274.653072
## iter 10 value 75.157817
## iter 20 value 67.715512
## iter 30 value 67.119159
## iter 40 value 67.096028
## iter 50 value 67.095826
## final value 67.095824
## converged
## # weights: 54 (34 variable)
## initial value 274.653072
## iter 10 value 70.585243
## iter 20 value 64.169595
## iter 30 value 63.518605
## iter 40 value 63.469793
## iter 50 value 63.468847
## final value 63.468843
## converged
## Df AIC
## <none> 194.19
## - zone.gp 6 194.74
## + time.day.gp 4 194.94
## - cat_pro.gp 4 195.23
## + a 4 195.43
## - classe_avis_pnm 2 198.07
## + res_tour 2 198.19
## - Temps_peche_estime.cat2h 2 199.09
## - age_classe 4 200.67
## - dep.mod_peche.chr 4 201.13
## - nb_sort_an_cat 4 205.73
## - poss_bat 2 303.26
stepwise_model.forward$call
## multinom(formula = mod_peche ~ poss_bat + age_classe + nb_sort_an_cat +
## dep.mod_peche.chr + Temps_peche_estime.cat2h + classe_avis_pnm +
## cat_pro.gp + zone.gp, data = df.mod.large)
stepwise_model.backward <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.large), direction = "backward")
## Start: AIC=447.16
## mod_peche ~ 1
stepwise_model.backward$call
## multinom(formula = mod_peche ~ 1, data = df.mod.large)
stepwise_model.both <- stepAIC(null_model, scope = list(lower = null_model, upper = multinom_model.large), direction = "both")
## Start: AIC=447.16
## mod_peche ~ 1
##
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 197.057558
## final value 197.053042
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## final value 221.301862
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## final value 219.966908
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 197.063658
## iter 20 value 196.477813
## iter 30 value 196.476702
## final value 196.472095
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 202.910938
## iter 20 value 202.676515
## final value 202.663441
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 208.878238
## iter 20 value 208.220177
## final value 208.197007
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 203.745306
## final value 203.742661
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 210.741239
## iter 20 value 210.308334
## final value 210.282872
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 167.988810
## iter 20 value 167.362387
## final value 167.286025
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 218.202664
## final value 218.202659
## converged
## Df AIC
## + poss_bat 2 224.55
## + dep.mod_peche.chr 4 346.57
## + a 4 406.11
## + zone.gp 6 408.94
## + age_classe 4 417.33
## + time.day.gp 4 419.49
## + cat_pro.gp 4 428.39
## + nb_sort_an_cat 4 432.57
## + classe_avis_pnm 2 444.41
## <none> 447.16
## + Temps_peche_estime.cat2h 2 447.93
## + res_tour 2 450.60
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
##
## Step: AIC=224.55
## mod_peche ~ poss_bat
##
## # weights: 6 (2 variable)
## initial value 274.653072
## final value 221.578178
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.561792
## final value 106.510950
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 108.268768
## final value 108.258547
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 105.778202
## final value 105.773207
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 103.245538
## iter 20 value 102.549576
## final value 102.545096
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 101.569368
## iter 20 value 100.309789
## iter 30 value 100.292327
## final value 100.291852
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 102.388445
## final value 102.349817
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.536089
## iter 20 value 101.389387
## iter 30 value 101.316024
## final value 101.314815
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 103.443206
## iter 20 value 102.777542
## iter 30 value 102.765320
## final value 102.764870
## converged
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 105.716608
## final value 105.705357
## converged
## Df AIC
## + age_classe 4 216.29
## + cat_pro.gp 4 216.58
## + nb_sort_an_cat 4 218.63
## + time.day.gp 4 220.70
## + dep.mod_peche.chr 4 221.53
## + classe_avis_pnm 2 223.41
## + Temps_peche_estime.cat2h 2 223.55
## <none> 224.55
## + zone.gp 6 225.09
## + res_tour 2 228.52
## + a 4 229.02
## - poss_bat 2 447.16
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
##
## Step: AIC=216.29
## mod_peche ~ poss_bat + age_classe
##
## # weights: 12 (6 variable)
## initial value 274.653072
## iter 10 value 202.910938
## iter 20 value 202.676515
## final value 202.663441
## converged
## # weights: 9 (4 variable)
## initial value 274.653072
## iter 10 value 108.854122
## final value 108.273897
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 96.517288
## iter 20 value 95.967321
## iter 30 value 95.955771
## final value 95.955761
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 100.428861
## iter 20 value 100.063801
## iter 30 value 100.057831
## iter 40 value 100.055700
## final value 100.055682
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 98.066402
## iter 20 value 97.411184
## iter 30 value 97.395156
## iter 40 value 97.391430
## final value 97.391341
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 95.580854
## iter 20 value 94.121933
## iter 30 value 94.095631
## final value 94.095620
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 97.088787
## iter 20 value 96.115318
## iter 30 value 96.090899
## iter 40 value 96.090307
## final value 96.089942
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 94.796583
## iter 20 value 94.225747
## iter 30 value 94.212187
## final value 94.212171
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.399464
## iter 20 value 94.335888
## iter 30 value 94.324995
## final value 94.324979
## converged
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 97.440295
## iter 20 value 97.106838
## iter 30 value 97.101498
## iter 40 value 97.099352
## final value 97.099317
## converged
## Df AIC
## + nb_sort_an_cat 4 208.61
## + time.day.gp 4 212.42
## + dep.mod_peche.chr 4 212.65
## + classe_avis_pnm 2 214.20
## + Temps_peche_estime.cat2h 2 214.78
## + a 4 215.91
## + cat_pro.gp 4 216.18
## + zone.gp 6 216.19
## <none> 216.29
## + res_tour 2 220.11
## - age_classe 4 224.55
## - poss_bat 2 417.33
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
##
## Step: AIC=208.61
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat
##
## # weights: 18 (10 variable)
## initial value 274.653072
## iter 10 value 194.992567
## iter 20 value 192.277323
## final value 192.272811
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 106.536089
## iter 20 value 101.389387
## iter 30 value 101.316024
## final value 101.314815
## converged
## # weights: 15 (8 variable)
## initial value 274.653072
## iter 10 value 100.385275
## iter 20 value 100.156836
## iter 30 value 100.147482
## final value 100.146995
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.511257
## iter 20 value 90.075201
## iter 30 value 90.042175
## final value 90.041999
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 93.651925
## iter 20 value 92.295985
## iter 30 value 92.240683
## final value 92.240647
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 91.658938
## iter 20 value 89.670365
## iter 30 value 89.555570
## iter 40 value 89.555488
## iter 50 value 89.554772
## final value 89.554690
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 89.952261
## iter 20 value 86.857659
## iter 30 value 86.788393
## final value 86.787513
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 89.755125
## iter 20 value 87.584774
## iter 30 value 87.506661
## final value 87.506108
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.214458
## iter 20 value 88.611164
## iter 30 value 88.559801
## iter 40 value 88.559550
## iter 40 value 88.559550
## iter 40 value 88.559550
## final value 88.559550
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 90.941388
## iter 20 value 89.654820
## iter 30 value 89.587298
## final value 89.587274
## converged
## Df AIC
## + dep.mod_peche.chr 4 200.62
## + cat_pro.gp 4 207.01
## + Temps_peche_estime.cat2h 2 207.11
## + classe_avis_pnm 2 207.17
## <none> 208.61
## + time.day.gp 4 209.12
## + zone.gp 6 209.58
## + a 4 212.08
## + res_tour 2 212.48
## - nb_sort_an_cat 4 216.29
## - age_classe 4 218.63
## - poss_bat 2 404.55
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
##
## Step: AIC=200.62
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr
##
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 147.259443
## iter 20 value 143.573206
## iter 30 value 143.548107
## final value 143.548085
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.874589
## iter 20 value 94.787853
## iter 30 value 94.733408
## iter 40 value 94.729991
## iter 50 value 94.729749
## final value 94.729729
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 95.399464
## iter 20 value 94.335888
## iter 30 value 94.324995
## final value 94.324979
## converged
## # weights: 21 (12 variable)
## initial value 274.653072
## iter 10 value 93.663625
## iter 20 value 92.329395
## iter 30 value 92.307421
## iter 40 value 92.307142
## iter 50 value 92.306574
## final value 92.306562
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 86.837732
## iter 20 value 82.479256
## iter 30 value 82.387856
## iter 40 value 82.387328
## final value 82.387325
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 86.739004
## iter 20 value 84.434189
## iter 30 value 84.300764
## final value 84.299630
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 86.217292
## iter 20 value 79.764922
## iter 30 value 79.431740
## iter 40 value 79.427352
## final value 79.427342
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.429772
## iter 20 value 80.127862
## iter 30 value 80.028891
## iter 40 value 80.027972
## final value 80.027968
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 83.779798
## iter 20 value 80.366096
## iter 30 value 80.240340
## iter 40 value 80.239380
## final value 80.239374
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 85.433497
## iter 20 value 81.656495
## iter 30 value 81.457614
## final value 81.454826
## converged
## Df AIC
## + Temps_peche_estime.cat2h 2 198.88
## + classe_avis_pnm 2 198.91
## + cat_pro.gp 4 200.06
## + time.day.gp 4 200.48
## <none> 200.62
## + zone.gp 6 202.85
## + res_tour 2 204.60
## + a 4 204.78
## - dep.mod_peche.chr 4 208.61
## - nb_sort_an_cat 4 212.65
## - age_classe 4 213.46
## - poss_bat 2 315.10
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
##
## Step: AIC=198.88
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h
##
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 144.786436
## iter 20 value 142.865929
## iter 30 value 142.840298
## final value 142.840221
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 94.077343
## iter 20 value 93.085401
## iter 30 value 93.057419
## final value 93.057418
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 93.346994
## iter 20 value 91.919583
## iter 30 value 91.842398
## final value 91.842375
## converged
## # weights: 24 (14 variable)
## initial value 274.653072
## iter 10 value 91.658938
## iter 20 value 89.670365
## iter 30 value 89.555570
## iter 40 value 89.555488
## iter 50 value 89.554772
## final value 89.554690
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 86.560363
## iter 20 value 84.366930
## iter 30 value 84.309477
## final value 84.309120
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 85.455932
## iter 20 value 79.975636
## iter 30 value 79.674216
## iter 40 value 79.669654
## final value 79.669622
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 90.305779
## iter 20 value 81.711648
## iter 30 value 81.424315
## iter 40 value 81.421155
## final value 81.421139
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 81.679078
## iter 20 value 75.845360
## iter 30 value 75.413375
## iter 40 value 75.403995
## final value 75.403967
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.825470
## iter 20 value 77.307926
## iter 30 value 76.853376
## iter 40 value 76.848188
## final value 76.848176
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.124585
## iter 20 value 77.381349
## iter 30 value 77.165242
## iter 40 value 77.159733
## final value 77.159711
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
## Df AIC
## + classe_avis_pnm 2 196.51
## + cat_pro.gp 4 197.70
## + time.day.gp 4 198.32
## + zone.gp 6 198.81
## <none> 198.88
## - Temps_peche_estime.cat2h 2 200.62
## + res_tour 2 202.84
## + a 4 203.34
## - dep.mod_peche.chr 4 207.11
## - nb_sort_an_cat 4 211.68
## - age_classe 4 214.11
## - poss_bat 2 317.68
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
##
## Step: AIC=196.51
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm
##
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 140.868043
## iter 20 value 139.559698
## iter 30 value 139.528212
## final value 139.528073
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 91.895481
## iter 20 value 90.162318
## iter 30 value 90.076490
## final value 90.075792
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 89.753479
## iter 20 value 88.605408
## iter 30 value 88.530092
## iter 40 value 88.529029
## final value 88.529025
## converged
## # weights: 27 (16 variable)
## initial value 274.653072
## iter 10 value 87.272451
## iter 20 value 86.550868
## iter 30 value 86.486138
## final value 86.485329
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 85.433497
## iter 20 value 81.656495
## iter 30 value 81.457614
## final value 81.454826
## converged
## # weights: 30 (18 variable)
## initial value 274.653072
## iter 10 value 84.663029
## iter 20 value 81.712863
## iter 30 value 81.443205
## final value 81.439508
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 80.992206
## iter 20 value 77.072663
## iter 30 value 76.834111
## iter 40 value 76.830467
## final value 76.830408
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 79.932898
## iter 20 value 78.381867
## iter 30 value 78.215932
## iter 40 value 78.197785
## final value 78.197662
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 78.710794
## iter 20 value 72.087606
## iter 30 value 71.632758
## iter 40 value 71.613465
## final value 71.613298
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 77.940965
## iter 20 value 74.113450
## iter 30 value 73.877129
## iter 40 value 73.874320
## final value 73.874260
## converged
## Df AIC
## + cat_pro.gp 4 194.74
## + zone.gp 6 195.23
## + time.day.gp 4 195.75
## <none> 196.51
## - classe_avis_pnm 2 198.88
## - Temps_peche_estime.cat2h 2 198.91
## + res_tour 2 200.40
## + a 4 201.66
## - dep.mod_peche.chr 4 204.97
## - nb_sort_an_cat 4 209.06
## - age_classe 4 212.15
## - poss_bat 2 315.06
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
##
## Step: AIC=194.74
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm + cat_pro.gp
##
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 136.257189
## iter 20 value 134.021670
## iter 30 value 133.886223
## iter 40 value 133.885300
## final value 133.885297
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 84.817178
## iter 20 value 81.013507
## iter 30 value 80.694870
## iter 40 value 80.689948
## final value 80.689927
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 98.992778
## iter 20 value 84.309239
## iter 30 value 84.169007
## iter 40 value 84.141697
## final value 84.141370
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 84.671483
## iter 20 value 81.247938
## iter 30 value 81.046946
## iter 40 value 81.021514
## final value 81.021437
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 85.118669
## iter 20 value 77.334869
## iter 30 value 76.912665
## iter 40 value 76.907503
## final value 76.907491
## converged
## # weights: 36 (22 variable)
## initial value 274.653072
## iter 10 value 82.825470
## iter 20 value 77.307926
## iter 30 value 76.853376
## iter 40 value 76.848188
## final value 76.848176
## converged
## # weights: 33 (20 variable)
## initial value 274.653072
## iter 10 value 85.693911
## iter 20 value 78.503990
## iter 30 value 78.258859
## iter 40 value 78.254293
## final value 78.254257
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 78.078561
## iter 20 value 72.012469
## iter 30 value 71.690963
## iter 40 value 71.670319
## final value 71.669418
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.921538
## iter 20 value 73.671272
## iter 30 value 73.276382
## iter 40 value 73.269860
## final value 73.269800
## converged
## # weights: 48 (30 variable)
## initial value 274.653072
## iter 10 value 73.959423
## iter 20 value 67.820214
## iter 30 value 67.117798
## iter 40 value 67.097084
## iter 50 value 67.096887
## iter 50 value 67.096887
## iter 50 value 67.096887
## final value 67.096887
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 79.788562
## iter 20 value 69.750226
## iter 30 value 69.278154
## iter 40 value 69.246797
## iter 50 value 69.245898
## final value 69.245891
## converged
## Df AIC
## + zone.gp 6 194.19
## + time.day.gp 4 194.49
## <none> 194.74
## - cat_pro.gp 4 196.51
## - classe_avis_pnm 2 197.70
## - Temps_peche_estime.cat2h 2 197.81
## + res_tour 2 198.54
## + a 4 199.34
## - age_classe 4 201.38
## - dep.mod_peche.chr 4 202.04
## - nb_sort_an_cat 4 208.28
## - poss_bat 2 311.77
## # weights: 48 (30 variable)
## initial value 274.653072
## iter 10 value 73.959423
## iter 20 value 67.820214
## iter 30 value 67.117798
## iter 40 value 67.097084
## iter 50 value 67.096887
## iter 50 value 67.096887
## iter 50 value 67.096887
## final value 67.096887
## converged
##
## Step: AIC=194.19
## mod_peche ~ poss_bat + age_classe + nb_sort_an_cat + dep.mod_peche.chr +
## Temps_peche_estime.cat2h + classe_avis_pnm + cat_pro.gp +
## zone.gp
##
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 128.617357
## iter 20 value 124.715722
## iter 30 value 123.647404
## iter 40 value 123.629623
## final value 123.629577
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.655015
## iter 20 value 74.841123
## iter 30 value 74.342046
## iter 40 value 74.333337
## final value 74.333275
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 83.410741
## iter 20 value 77.307366
## iter 30 value 76.879191
## iter 40 value 76.865496
## final value 76.865437
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 79.456091
## iter 20 value 74.990185
## iter 30 value 74.581305
## iter 40 value 74.566817
## final value 74.566730
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 77.541715
## iter 20 value 71.998764
## iter 30 value 71.551022
## iter 40 value 71.542406
## final value 71.542369
## converged
## # weights: 45 (28 variable)
## initial value 274.653072
## iter 10 value 79.662192
## iter 20 value 71.597245
## iter 30 value 71.048090
## iter 40 value 71.036451
## final value 71.036418
## converged
## # weights: 42 (26 variable)
## initial value 274.653072
## iter 10 value 78.710794
## iter 20 value 72.087606
## iter 30 value 71.632758
## iter 40 value 71.613465
## final value 71.613298
## converged
## # weights: 39 (24 variable)
## initial value 274.653072
## iter 10 value 85.447527
## iter 20 value 73.755532
## iter 30 value 73.383599
## iter 40 value 73.368908
## final value 73.368633
## converged
## # weights: 54 (34 variable)
## initial value 274.653072
## iter 10 value 74.508734
## iter 20 value 64.493390
## iter 30 value 63.816995
## iter 40 value 63.716597
## iter 50 value 63.715659
## final value 63.715644
## converged
## # weights: 51 (32 variable)
## initial value 274.653072
## iter 10 value 75.157817
## iter 20 value 67.715512
## iter 30 value 67.119159
## iter 40 value 67.096028
## iter 50 value 67.095826
## final value 67.095824
## converged
## # weights: 54 (34 variable)
## initial value 274.653072
## iter 10 value 70.585243
## iter 20 value 64.169595
## iter 30 value 63.518605
## iter 40 value 63.469793
## iter 50 value 63.468847
## final value 63.468843
## converged
## Df AIC
## <none> 194.19
## - zone.gp 6 194.74
## + time.day.gp 4 194.94
## - cat_pro.gp 4 195.23
## + a 4 195.43
## - classe_avis_pnm 2 198.07
## + res_tour 2 198.19
## - Temps_peche_estime.cat2h 2 199.09
## - age_classe 4 200.67
## - dep.mod_peche.chr 4 201.13
## - nb_sort_an_cat 4 205.73
## - poss_bat 2 303.26
stepwise_model.both$call
## multinom(formula = mod_peche ~ poss_bat + age_classe + nb_sort_an_cat +
## dep.mod_peche.chr + Temps_peche_estime.cat2h + classe_avis_pnm +
## cat_pro.gp + zone.gp, data = df.mod.large)
stepwise_model.forward$call
## multinom(formula = mod_peche ~ poss_bat + age_classe + nb_sort_an_cat +
## dep.mod_peche.chr + Temps_peche_estime.cat2h + classe_avis_pnm +
## cat_pro.gp + zone.gp, data = df.mod.large)
stepwise_model.backward$call
## multinom(formula = mod_peche ~ 1, data = df.mod.large)
stepwise_model.both$call
## multinom(formula = mod_peche ~ poss_bat + age_classe + nb_sort_an_cat +
## dep.mod_peche.chr + Temps_peche_estime.cat2h + classe_avis_pnm +
## cat_pro.gp + zone.gp, data = df.mod.large)
# fit with variables that have a significant effect on the dependant variable mod_peche
multinom_model.large.red <- multinom(mod_peche ~ . -a -res_tour -time.day.gp
#- poss_bat -res_tour -classe_avis_pnm -Temps_peche_estime.cat2h
, data = df.mod.large) # obviously cat_pro.gp still ameliorate the model although not having a significant effect so keep it as well
## # weights: 48 (30 variable)
## initial value 274.653072
## iter 10 value 73.959423
## iter 20 value 67.820214
## iter 30 value 67.117798
## iter 40 value 67.097084
## iter 50 value 67.096887
## iter 50 value 67.096887
## iter 50 value 67.096887
## final value 67.096887
## converged
summary(multinom_model.large.red)
## Call:
## multinom(formula = mod_peche ~ . - a - res_tour - time.day.gp,
## data = df.mod.large)
##
## Coefficients:
## (Intercept) Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine -22.45092 1.264743 18.668746
## peche embarquée -6.75013 3.148687 -2.304378
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 19.380514 18.9756917 -1.683081
## peche embarquée -1.340383 -0.7676765 1.732331
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine -4.132878 -23.0128493
## peche embarquée 4.148170 -0.7480734
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine -0.3108234 2.447436
## peche embarquée -0.2145241 6.867194
## nb_sort_an_catQ2 (16-30) nb_sort_an_catQ3 (>=31)
## chasse sous-marine -16.07140793 -1.774175
## peche embarquée -0.08024469 -3.173750
## dep.mod_peche.chr> 2000 euros
## chasse sous-marine -16.80063
## peche embarquée 3.49910
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.188582 2.800167
## peche embarquée 1.098705 1.544719
##
## Std. Errors:
## (Intercept) Temps_peche_estime.cat2h>=2h zone.gpEst-Nord Cap
## chasse sous-marine 1.290751 1.113411 0.7289207
## peche embarquée 1.877578 1.119467 0.9149654
## zone.gpnimp_ou zone.gpOuest-Nord Cap age_classe40-59
## chasse sous-marine 0.8512296 1.069913 0.6848471
## peche embarquée 1.0654278 1.225692 1.0660759
## age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 7.668693e-11 4.550311e-10
## peche embarquée 1.877818e+00 8.171878e-01
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine 0.8637343 1.185732
## peche embarquée 1.2277400 1.122408
## nb_sort_an_catQ2 (16-30) nb_sort_an_catQ3 (>=31)
## chasse sous-marine 1.137615e-06 1.014059
## peche embarquée 9.668382e-01 1.096197
## dep.mod_peche.chr> 2000 euros
## chasse sous-marine 1.901392e-07
## peche embarquée 1.491934e+00
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 1.0869288 1.301851
## peche embarquée 0.9067243 1.215777
##
## Residual Deviance: 134.1938
## AIC: 194.1938
#interpret the coefficients in terms of odds ratios
exp(coef(multinom_model.large.red))
## (Intercept) Temps_peche_estime.cat2h>=2h
## chasse sous-marine 1.776999e-10 3.542182
## peche embarquée 1.170728e-03 23.305439
## zone.gpEst-Nord Cap zone.gpnimp_ou zone.gpOuest-Nord Cap
## chasse sous-marine 1.281543e+08 2.611260e+08 1.741960e+08
## peche embarquée 9.982091e-02 2.617454e-01 4.640901e-01
## age_classe40-59 age_classe60 et plus cat_pro.gpretraite
## chasse sous-marine 0.1858006 0.01603666 1.013087e-10
## peche embarquée 5.6538171 63.31804731 4.732775e-01
## cat_pro.gpsans_emploi-en_arret-etudiant poss_batoui
## chasse sous-marine 0.7328433 11.55867
## peche embarquée 0.8069254 960.25055
## nb_sort_an_catQ2 (16-30) nb_sort_an_catQ3 (>=31)
## chasse sous-marine 1.047795e-07 0.16962340
## peche embarquée 9.228905e-01 0.04184638
## dep.mod_peche.chr> 2000 euros
## chasse sous-marine 5.053358e-08
## peche embarquée 3.308566e+01
## dep.mod_peche.chrentre 500-2000 euros classe_avis_pnmpositif
## chasse sous-marine 3.282425 16.447396
## peche embarquée 3.000277 4.686652
(multinom.tbl.large.red <- tidy(multinom_model.large.red, conf.int = TRUE))
## # A tibble: 30 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -22.5 1.29e+ 0 -1.74e+ 1 9.21e- 68 -25.0 -19.9
## 2 chasse sous-… Temp… 1.26 1.11e+ 0 1.14e+ 0 2.56e- 1 -0.918 3.45
## 3 chasse sous-… zone… 18.7 7.29e- 1 2.56e+ 1 1.14e-144 17.2 20.1
## 4 chasse sous-… zone… 19.4 8.51e- 1 2.28e+ 1 9.59e-115 17.7 21.0
## 5 chasse sous-… zone… 19.0 1.07e+ 0 1.77e+ 1 2.22e- 70 16.9 21.1
## 6 chasse sous-… age_… -1.68 6.85e- 1 -2.46e+ 0 1.40e- 2 -3.03 -0.341
## 7 chasse sous-… age_… -4.13 7.67e-11 -5.39e+10 0 -4.13 -4.13
## 8 chasse sous-… cat_… -23.0 4.55e-10 -5.06e+10 0 -23.0 -23.0
## 9 chasse sous-… cat_… -0.311 8.64e- 1 -3.60e- 1 7.19e- 1 -2.00 1.38
## 10 chasse sous-… poss… 2.45 1.19e+ 0 2.06e+ 0 3.90e- 2 0.123 4.77
## # ℹ 20 more rows
write.csv2(multinom.tbl.large.red, "Tables/Regression/multinom.2020-2022.csv", row.names = F)
(multinom.tbl.large.red.sign <- filter(multinom.tbl.large.red, p.value < 0.05))
## # A tibble: 18 × 8
## y.level term estimate std.error statistic p.value conf.low conf.high
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 chasse sous-… (Int… -22.5 1.29e+ 0 -1.74e 1 9.21e- 68 -25.0 -19.9
## 2 chasse sous-… zone… 18.7 7.29e- 1 2.56e 1 1.14e-144 17.2 20.1
## 3 chasse sous-… zone… 19.4 8.51e- 1 2.28e 1 9.59e-115 17.7 21.0
## 4 chasse sous-… zone… 19.0 1.07e+ 0 1.77e 1 2.22e- 70 16.9 21.1
## 5 chasse sous-… age_… -1.68 6.85e- 1 -2.46e 0 1.40e- 2 -3.03 -0.341
## 6 chasse sous-… age_… -4.13 7.67e-11 -5.39e10 0 -4.13 -4.13
## 7 chasse sous-… cat_… -23.0 4.55e-10 -5.06e10 0 -23.0 -23.0
## 8 chasse sous-… poss… 2.45 1.19e+ 0 2.06e 0 3.90e- 2 0.123 4.77
## 9 chasse sous-… nb_s… -16.1 1.14e- 6 -1.41e 7 0 -16.1 -16.1
## 10 chasse sous-… dep.… -16.8 1.90e- 7 -8.84e 7 0 -16.8 -16.8
## 11 chasse sous-… clas… 2.80 1.30e+ 0 2.15e 0 3.15e- 2 0.249 5.35
## 12 peche embarq… (Int… -6.75 1.88e+ 0 -3.60e 0 3.24e- 4 -10.4 -3.07
## 13 peche embarq… Temp… 3.15 1.12e+ 0 2.81e 0 4.91e- 3 0.955 5.34
## 14 peche embarq… zone… -2.30 9.15e- 1 -2.52e 0 1.18e- 2 -4.10 -0.511
## 15 peche embarq… age_… 4.15 1.88e+ 0 2.21e 0 2.72e- 2 0.468 7.83
## 16 peche embarq… poss… 6.87 1.12e+ 0 6.12e 0 9.46e- 10 4.67 9.07
## 17 peche embarq… nb_s… -3.17 1.10e+ 0 -2.90e 0 3.79e- 3 -5.32 -1.03
## 18 peche embarq… dep.… 3.50 1.49e+ 0 2.35e 0 1.90e- 2 0.575 6.42
# watch video https://www.youtube.com/watch?v=oxRy2DMrOF4 on how to write the model to add it in a report
(mod1vs2 <- paste0("ln[P(mod_peche=2)/P(mod_peche=1)] = ", (exp(coef(multinom_model.large.red)))[1,1], " + " , (exp(coef(multinom_model.large.red)))[1,2],"*",colnames(exp(coef(multinom_model.large.red)))[2], " + ", (exp(coef(multinom_model.large.red)))[1,3],"*",colnames(exp(coef(multinom_model.large.red)))[3], " + ..."))
## [1] "ln[P(mod_peche=2)/P(mod_peche=1)] = 1.77699930662846e-10 + 3.54218245197893*Temps_peche_estime.cat2h>=2h + 128154331.359266*zone.gpEst-Nord Cap + ..."
writeLines(mod1vs2, "Tables/Regression/multinom.2020-2022.P1vsP2.txt")
(mod1vs3 <- paste0("ln[P(mod_peche=3)/P(mod_peche=1)] = ", (exp(coef(multinom_model.large.red)))[2,1], " + " , (exp(coef(multinom_model.large.red)))[2,2],"*",colnames(exp(coef(multinom_model.large.red)))[2], " + ", (exp(coef(multinom_model.large.red)))[2,3],"*",colnames(exp(coef(multinom_model.large.red)))[3], " + ..."))
## [1] "ln[P(mod_peche=3)/P(mod_peche=1)] = 0.001170727828064 + 23.3054386684543*Temps_peche_estime.cat2h>=2h + 0.0998209115307417*zone.gpEst-Nord Cap + ..."
writeLines(mod1vs3, "Tables/Regression/multinom.2020-2022.P1vsP3.txt")
# Fit a decision tree
# http://www.milbo.org/rpart-plot/prp.pdf
tree_model <- rpart(mod_peche ~ . -a -res_tour -time.day.gp
#- poss_bat -res_tour -classe_avis_pnm -Temps_peche_estime.cat2h
, data = df.mod.large, method = "class")
rpart.plot(tree_model, type = 4, extra = 2)
# we have to remove poss_bat, cfr of course any fisher with a boat does peche embarquee
tree_model <- rpart(mod_peche ~ . -a -res_tour -time.day.gp
- poss_bat
#-res_tour -classe_avis_pnm -Temps_peche_estime.cat2h
, data = df.mod.large, method = "class")
rpart.plot(tree_model, type = 4, extra = 2)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red")))
# plot Kiviat diagram ####
#2020-2022
df.full <- na.omit(filter(df.msa[, c(
"a",
"mod_peche",
"sexe",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp",
"age_classe",
"cat_pro.gp",
"nb_sort_an_cat",
"classe_avis_pnm",
"poss_bat",
"time.day.gp",
#"dep.median.rd.chr",
"dep.mod_peche.chr")
], a %in% c("2020", "2021", "2022")))
#df.full <- filter(df.full, cat_pro.gp != "etudiant")
#df.full <- filter(df.full, age_classe != "13-24")
#df.full <- filter(df.full, mod_peche != "peche à l'oursin")
#2020-2023
df.red <- na.omit(filter(df.msa[, c("a",
"mod_peche",
"sexe",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp")
], a %in% c("2020", "2021", "2022", "2023")))
#df.red <- filter(df.red, mod_peche != "peche à l'oursin")
# Calculer les pourcentages pour les catégories
df_summary <- as.data.frame(sapply(
#df.[, c("mod_peche", "nb_sort_an_cat", "classe_avis_pnm", "zone")],
df.full, function(x) sort(table(x)/length(x)))[1][1])
df.radar <- df.full #df.[, c("mod_peche","age_classe","cat_pro","classe_avis_pnm","zone","nb_sort_an_cat")]
p.radar <- data.frame(matrix(nrow = 2, ncol = ncol(df.full)))
colnames(p.radar) <- names(df.full) #c("mod_peche","age_classe","cat_pro","classe_avis_pnm","zone","nb_sort_an_cat")
for (i in 1:ncol(df.radar)) {
#i=1
p.radar[1, names(df.radar)[i]] <- paste0(names(sort(table(na.omit(df.radar[, i]))/length(na.omit(df.radar[, i])), decreasing = T)[1]), " (n=", length(na.omit(df.radar[, i])), ")")
p.radar[2, names(df.radar)[i]] <- sort(table(na.omit(df.radar[, i]))/length(na.omit(df.radar[, i])), decreasing = T)[1]
}
names(p.radar) <- p.radar[1,]
p.radar <- p.radar[-1,]
p.radar <- rbind(0,p.radar)
p.radar <- rbind(1,p.radar)
p.radar <- lapply(p.radar,as.numeric)
names.radar <- names(p.radar)
p.radar <- data.frame(p.radar)
names(p.radar) <- names.radar
#write.csv2(p.radar, "p.radar.csv") #for ChatGPT
radarchart(p.radar
, axistype=1
, pcol=rgb(0.2,0.5,0.5,0.9)
, pfcol=rgb(0.2,0.5,0.5,0.5)
, plwd=4
#, cglcol="grey"
, cglty=1
, axislabcol="grey"
, caxislabels= c(0, 20, 50, 75, 100)
, cglwd=0.8
, vlcex=1
, title = "trois mode de peche confondus, 2020-2022"
)
plot.radar <- function(col., col.fill, title.) {
p.radar <- data.frame(matrix(nrow = 2, ncol = ncol(df.plora))) # define df.radar prior ruuning the function
colnames(p.radar) <- names(df.plora) #c("mode_peche","age_classe","cat_pro","classe_avis_pnm","zone","nb_sort_an_cat"
for (i in 1:ncol(df.plora)) {
#i=1
#df.plora = df.radar.pdb
#col. = "#F8766D"
#col.fill = "#F8766D50"
#title. = "peche du bord"
p.radar[1, names(df.plora)[i]] <- paste0(names(sort(table(na.omit(df.plora[, i]))/length(na.omit(df.plora[, i])), decreasing = T)[1]), " (n=", length(na.omit(df.plora[, i])), ")")
p.radar[2, names(df.plora)[i]] <- sort(table(na.omit(df.plora[, i]))/length(na.omit(df.plora[, i])), decreasing = T)[1]
}
names(p.radar) <- p.radar[1,]
p.radar <- p.radar[-1,]
p.radar <- rbind(0,p.radar)
p.radar <- rbind(1,p.radar)
p.radar <- lapply(p.radar,as.numeric)
names.radar <- names(p.radar)
p.radar <- data.frame(p.radar)
names(p.radar) <- names.radar
#write.csv2(p.radar, "p.radar.csv") #for ChatGPT
p.radar <- within(p.radar, rm("NA"))
radarchart(p.radar
, axistype=1
, pcol=col. #rgb(0.2,0.5,0.5,0.9)
, pfcol=col.fill #rgb(0.2,0.5,0.5,0.5)
, plwd=4
#, cglcol="grey"
, cglty=1
, axislabcol="grey"
, caxislabels= c(0, 20, 50, 75, 100)
, cglwd=0.8
, vlcex=1
, title = title.
)
}
op <- par(mar = c(0, 2, 2, 2))
par(mfrow = c(3,1))
df.plora <- df.full
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## 4 Levels: chasse sous-marine peche du bord ... peche à l'oursin
unique(df.plora$a)
## [1] 2020 2021 2022
## Levels: 2020 2021 2022
plot.radar(col. = "#F8766D", col.fill = "#F8766D50", title. = "trois mode de peche confondus, 2020-2022")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- df.red
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche du bord chasse sous-marine peche embarquée peche à l'oursin
## 4 Levels: chasse sous-marine peche du bord ... peche à l'oursin
unique(df.plora$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
plot.radar(col. = "#00BA38", col.fill = "#00BA3850", title. = "trois mode de peche confondus, 2020-2023")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.red, a == "2023")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche embarquée peche du bord chasse sous-marine
## Levels: chasse sous-marine peche du bord peche embarquée
unique(df.plora$a)
## [1] 2023
## Levels: 2023
plot.radar(col. = "#619CFF", col.fill = "#619CFF50", title. = "trois mode de peche confondus, 2023")
## Warning in rm("NA"): objet 'NA' introuvable
#ggsave("Figs/Kiviat/kiviat_3.png", width = 5, height = 15) #ggsave doesn't work, do it manually; 400x1200 ; idem for the next ones
par(op)
par(mfrow = c(1,1))
op <- par(mar = c(0, 2, 2, 2))
par(mfrow = c(3,1))
df.plora <- filter(df.full, mod_peche == "peche du bord")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche du bord
## Levels: peche du bord
unique(df.plora$a)
## [1] 2020 2021 2022
## Levels: 2020 2021 2022
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#F8766D", col.fill = "#F8766D50", title. = "peche du bord, 2020-2022")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.full, mod_peche == "peche embarquée")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche embarquée
## Levels: peche embarquée
unique(df.plora$a)
## [1] 2020 2021 2022
## Levels: 2020 2021 2022
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#00BA38", col.fill = "#00BA3850", title. = "peche embarquée, 2020-2022")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.full, mod_peche == "chasse sous-marine")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] chasse sous-marine
## Levels: chasse sous-marine
unique(df.plora$a)
## [1] 2020 2021 2022
## Levels: 2020 2021 2022
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#619CFF", col.fill = "#619CFF50", title. = "chasse sous-marine, 2020-2022")
## Warning in rm("NA"): objet 'NA' introuvable
par(op)
par(mfrow = c(1,1))
op <- par(mar = c(0, 2, 2, 2))
par(mfrow = c(3,1))
df.plora <- filter(df.red, mod_peche == "peche du bord")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche du bord
## Levels: peche du bord
unique(df.plora$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#F8766D", col.fill = "#F8766D50", title. = "peche du bord, 2020-2023")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.red, mod_peche == "peche embarquée")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche embarquée
## Levels: peche embarquée
unique(df.plora$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#00BA38", col.fill = "#00BA3850", title. = "peche embarquée, 2020-2023")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.red, mod_peche == "chasse sous-marine")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] chasse sous-marine
## Levels: chasse sous-marine
unique(df.plora$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#619CFF", col.fill = "#619CFF50", title. = "chasse sous-marine, 2020-2023")
## Warning in rm("NA"): objet 'NA' introuvable
par(op)
par(mfrow = c(1,1))
op <- par(mar = c(0, 2, 2, 2))
par(mfrow = c(3,1))
df.plora <- filter(df.red, mod_peche == "peche du bord", a == "2023")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche du bord
## Levels: peche du bord
unique(df.plora$a)
## [1] 2023
## Levels: 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#F8766D", col.fill = "#F8766D50", title. = "peche du bord, 2023")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.red, mod_peche == "peche embarquée", a == "2023")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] peche embarquée
## Levels: peche embarquée
unique(df.plora$a)
## [1] 2023
## Levels: 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#00BA38", col.fill = "#00BA3850", title. = "peche embarquée, 2023")
## Warning in rm("NA"): objet 'NA' introuvable
df.plora <- filter(df.red, mod_peche == "chasse sous-marine", a == "2023")
df.plora <- droplevels(df.plora)
unique(df.plora$mod_peche)
## [1] chasse sous-marine
## Levels: chasse sous-marine
unique(df.plora$a)
## [1] 2023
## Levels: 2023
df.plora <- df.plora[ , -which(names(df.plora) %in% c("mod_peche"))]
plot.radar(col. = "#619CFF", col.fill = "#619CFF50", title. = "chasse sous-marine, 2023")
## Warning in rm("NA"): objet 'NA' introuvable
par(op)
par(mfrow = c(1,1))
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red")))
# table enquête en ligne + figs ####
# I will now work with the df.full df. of above multivariate spatial analysis and Kiviat diagrams.
# so all the previous code was removed, copy paste in another R script just in case, but always available in the above code since same preparation work of variables.
# Function to calculate percentages for each categorical variable
calculate_percentages <- function(df.red) {
tbl <- table(df.red)
perc <- prop.table(tbl) * 100
return(perc)
}
# Function to calculate occurence for each categorical variable
calculate_occurences <- function(df.red) {
tbl <- table(df.red)
return(tbl)
}
# I will here rename the df of above multivariate spatial analysis in order not to change the script below
unique(df.msa$a)
## [1] 2020 2021 2022 2023 <NA> 2024
## Levels: 2020 2021 2022 2023 2024
df.red <- #na.omit
(filter(df.msa[, c(
"a",
"mod_peche",
"sexe",
"res_tour",
"Temps_peche_estime.cat2h",
"zone.gp",
"age_classe",
"cat_pro.gp",
"nb_sort_an_cat",
"classe_avis_pnm",
"poss_bat",
"time.day.gp",
#"dep.median.rd.chr",
"dep.mod_peche.chr")
], a %in% c("2020", "2021", "2022", "2023")))
df.red <- droplevels(df.red) # year 2023 removed when na.omit cfr many variables without data
unique(df.red$a)
## [1] 2020 2021 2022 2023
## Levels: 2020 2021 2022 2023
# Apply this function to each column in the DataFrame
# Use sapply if you want a list of results for each column
percentage_results <- sapply(df.red, calculate_percentages)
occurence_results <- sapply(df.red, calculate_occurences)
#saveRDS(percentage_results, "percentage_results.rds") #for ChatGPT
# Display the results
print(percentage_results)
## $a
## df.red
## 2020 2021 2022 2023
## 23.55658 17.09007 19.63048 39.72286
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 8.5450346 57.2748268 33.7182448 0.4618938
##
## $sexe
## df.red
## femme homme
## 3.464203 96.535797
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 6.004619 73.672055 5.773672 14.549654
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 12.00924 87.99076
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 1.388889 44.675926 35.185185 1.388889 6.481481
## Saint-Florent
## 10.879630
##
## $age_classe
## df.red
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 1.923077 15.384615 23.461538 44.615385 8.461538 6.153846
##
## $cat_pro.gp
## df.red
## activite etudiant retraite
## 51.538462 1.538462 37.692308
## sans_emploi-en_arret
## 9.230769
##
## $nb_sort_an_cat
## df.red
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 26.81992 30.26820 20.30651 22.60536
##
## $classe_avis_pnm
## df.red
## negatif p_avis positif
## 0.7692308 15.3846154 83.8461538
##
## $poss_bat
## df.red
## non oui
## 52.87356 47.12644
##
## $time.day.gp
## df.red
## am journee nimp_q nuit pm
## 51.5384615 3.4615385 32.6923077 0.3846154 11.9230769
##
## $dep.mod_peche.chr
## df.red
## < 100 euros entre 100-500 euros entre 1000-2000 euros
## 36.434109 22.868217 9.689922
## entre 500-1000 euros supérieur à 2000
## 11.240310 19.767442
results_perc <- do.call(rbind, lapply(percentage_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
print(occurence_results)
## $a
## df.red
## 2020 2021 2022 2023
## 102 74 85 172
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 37 248 146 2
##
## $sexe
## df.red
## femme homme
## 15 418
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 26 319 25 63
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 52 381
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 6 193 152 6 28
## Saint-Florent
## 47
##
## $age_classe
## df.red
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 5 40 61 116 22 16
##
## $cat_pro.gp
## df.red
## activite etudiant retraite
## 134 4 98
## sans_emploi-en_arret
## 24
##
## $nb_sort_an_cat
## df.red
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 70 79 53 59
##
## $classe_avis_pnm
## df.red
## negatif p_avis positif
## 2 40 218
##
## $poss_bat
## df.red
## non oui
## 138 123
##
## $time.day.gp
## df.red
## am journee nimp_q nuit pm
## 134 9 85 1 31
##
## $dep.mod_peche.chr
## df.red
## < 100 euros entre 100-500 euros entre 1000-2000 euros
## 94 59 25
## entre 500-1000 euros supérieur à 2000
## 29 51
results_occ <- do.call(rbind, lapply(occurence_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
results_df <- bind_cols(results_perc, results_occ)
## New names:
## • `Var1` -> `Var1...1`
## • `df.red` -> `df.red...2`
## • `Freq` -> `Freq...3`
## • `Var1` -> `Var1...4`
## • `df.red` -> `df.red...5`
## • `Freq` -> `Freq...6`
setdiff(results_df$df.red...2, results_df$df.red...5)
## character(0)
results_df <- results_df[, c(1,2,3,6)]
results_df$Var1...1 <- rownames(results_df)
results_df$Var1...1 <- str_sub(results_df$Var1, end=-3)
names(results_df)[names(results_df) == "Var1...1"] <- "parametre"
names(results_df)[names(results_df) == "df.red...2"] <- "categorie"
names(results_df)[names(results_df) == "Freq...3"] <- "pourcentage"
names(results_df)[names(results_df) == "Freq...6"] <- "n"
results_df %>% group_by(parametre) %>% summarise(N = sum(n, na.rm = T)) -> N
results_df <- left_join(results_df, N)
## Joining with `by = join_by(parametre)`
results_df
## parametre categorie pourcentage n N
## 1 a 2020 23.5565820 102 433
## 2 a 2021 17.0900693 74 433
## 3 a 2022 19.6304850 85 433
## 4 a 2023 39.7228637 172 433
## 5 mod_peche chasse sous-marine 8.5450346 37 433
## 6 mod_peche peche du bord 57.2748268 248 433
## 7 mod_peche peche embarquée 33.7182448 146 433
## 8 mod_peche peche à l'oursin 0.4618938 2 433
## 9 sexe femme 3.4642032 15 433
## 10 sexe homme 96.5357968 418 433
## 11 res_tour occasionnel 6.0046189 26 433
## 12 res_tour resident 73.6720554 319 433
## 13 res_tour secondaire 5.7736721 25 433
## 14 res_tour touriste 14.5496536 63 433
## 15 Temps_peche_estime.cat2h <2h 12.0092379 52 433
## 16 Temps_peche_estime.cat2h >=2h 87.9907621 381 433
## 17 zone.gp Agriates 1.3888889 6 432
## 18 zone.gp Est Cap 44.6759259 193 432
## 19 zone.gp nimp_ou 35.1851852 152 432
## 20 zone.gp Nord Cap 1.3888889 6 432
## 21 zone.gp Ouest Cap 6.4814815 28 432
## 22 zone.gp Saint-Florent 10.8796296 47 432
## 23 age_classe 13-24 1.9230769 5 260
## 24 age_classe 25-39 15.3846154 40 260
## 25 age_classe 40-49 23.4615385 61 260
## 26 age_classe 50-59 44.6153846 116 260
## 27 age_classe 60-69 8.4615385 22 260
## 28 age_classe 70 et plus 6.1538462 16 260
## 29 cat_pro.gp activite 51.5384615 134 260
## 30 cat_pro.gp etudiant 1.5384615 4 260
## 31 cat_pro.gp retraite 37.6923077 98 260
## 32 cat_pro.gp sans_emploi-en_arret 9.2307692 24 260
## 33 nb_sort_an_cat Q1 (<=10) 26.8199234 70 261
## 34 nb_sort_an_cat Q2 (11-15) 30.2681992 79 261
## 35 nb_sort_an_cat Q3 (16-30) 20.3065134 53 261
## 36 nb_sort_an_cat Q4 (>=31) 22.6053640 59 261
## 37 classe_avis_pnm negatif 0.7692308 2 260
## 38 classe_avis_pnm p_avis 15.3846154 40 260
## 39 classe_avis_pnm positif 83.8461538 218 260
## 40 poss_bat non 52.8735632 138 261
## 41 poss_bat oui 47.1264368 123 261
## 42 time.day.gp am 51.5384615 134 260
## 43 time.day.gp journee 3.4615385 9 260
## 44 time.day.gp nimp_q 32.6923077 85 260
## 45 time.day.gp nuit 0.3846154 1 260
## 46 time.day.gp pm 11.9230769 31 260
## 47 dep.mod_peche.chr < 100 euros 36.4341085 94 258
## 48 dep.mod_peche.chr entre 100-500 euros 22.8682171 59 258
## 49 dep.mod_peche.chr entre 1000-2000 euros 9.6899225 25 258
## 50 dep.mod_peche.chr entre 500-1000 euros 11.2403101 29 258
## 51 dep.mod_peche.chr supérieur à 2000 19.7674419 51 258
write.csv2(results_df, "Tables/Summary/summary_prop_2020-2023.csv", row.names = F)
df.1 <- filter(df.red, a %in% c("2020", "2021", "2022"))
df.1 <- droplevels(df.1)
percentage_results <- sapply(df.1, calculate_percentages)
occurence_results <- sapply(df.1, calculate_occurences)
#saveRDS(percentage_results, "percentage_results.rds") #for ChatGPT
# Display the results
print(percentage_results)
## $a
## df.red
## 2020 2021 2022
## 39.08046 28.35249 32.56705
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 6.1302682 44.8275862 48.2758621 0.7662835
##
## $sexe
## df.red
## femme homme
## 2.681992 97.318008
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 9.578544 78.160920 6.513410 5.747126
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 10.72797 89.27203
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 1.915709 43.678161 32.183908 1.915709 9.578544
## Saint-Florent
## 10.727969
##
## $age_classe
## df.red
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 1.923077 15.384615 23.461538 44.615385 8.461538 6.153846
##
## $cat_pro.gp
## df.red
## activite etudiant retraite
## 51.538462 1.538462 37.692308
## sans_emploi-en_arret
## 9.230769
##
## $nb_sort_an_cat
## df.red
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 26.81992 30.26820 20.30651 22.60536
##
## $classe_avis_pnm
## df.red
## negatif p_avis positif
## 0.7692308 15.3846154 83.8461538
##
## $poss_bat
## df.red
## non oui
## 52.87356 47.12644
##
## $time.day.gp
## df.red
## am journee nimp_q nuit pm
## 51.5384615 3.4615385 32.6923077 0.3846154 11.9230769
##
## $dep.mod_peche.chr
## df.red
## < 100 euros entre 100-500 euros entre 1000-2000 euros
## 36.434109 22.868217 9.689922
## entre 500-1000 euros supérieur à 2000
## 11.240310 19.767442
results_perc <- do.call(rbind, lapply(percentage_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
print(occurence_results)
## $a
## df.red
## 2020 2021 2022
## 102 74 85
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 16 117 126 2
##
## $sexe
## df.red
## femme homme
## 7 254
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 25 204 17 15
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 28 233
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 5 114 84 5 25
## Saint-Florent
## 28
##
## $age_classe
## df.red
## 13-24 25-39 40-49 50-59 60-69 70 et plus
## 5 40 61 116 22 16
##
## $cat_pro.gp
## df.red
## activite etudiant retraite
## 134 4 98
## sans_emploi-en_arret
## 24
##
## $nb_sort_an_cat
## df.red
## Q1 (<=10) Q2 (11-15) Q3 (16-30) Q4 (>=31)
## 70 79 53 59
##
## $classe_avis_pnm
## df.red
## negatif p_avis positif
## 2 40 218
##
## $poss_bat
## df.red
## non oui
## 138 123
##
## $time.day.gp
## df.red
## am journee nimp_q nuit pm
## 134 9 85 1 31
##
## $dep.mod_peche.chr
## df.red
## < 100 euros entre 100-500 euros entre 1000-2000 euros
## 94 59 25
## entre 500-1000 euros supérieur à 2000
## 29 51
results_occ <- do.call(rbind, lapply(occurence_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
results_df.1 <- bind_cols(results_perc, results_occ)
## New names:
## • `Var1` -> `Var1...1`
## • `df.red` -> `df.red...2`
## • `Freq` -> `Freq...3`
## • `Var1` -> `Var1...4`
## • `df.red` -> `df.red...5`
## • `Freq` -> `Freq...6`
setdiff(results_df.1$df.1red...2, results_df.1$df.1red...5)
## NULL
results_df.1 <- results_df.1[, c(1,2,3,6)]
results_df.1$Var1...1 <- rownames(results_df.1)
results_df.1$Var1...1 <- str_sub(results_df.1$Var1, end=-3)
names(results_df.1)[names(results_df.1) == "Var1...1"] <- "parametre"
names(results_df.1)[names(results_df.1) == "df.red...2"] <- "categorie"
names(results_df.1)[names(results_df.1) == "Freq...3"] <- "pourcentage"
names(results_df.1)[names(results_df.1) == "Freq...6"] <- "n"
results_df.1 %>% group_by(parametre) %>% summarise(N = sum(n, na.rm = T)) -> N
results_df.1 <- left_join(results_df.1, N)
## Joining with `by = join_by(parametre)`
results_df.1
## parametre categorie pourcentage n N
## 1 a 2020 39.0804598 102 261
## 2 a 2021 28.3524904 74 261
## 3 a 2022 32.5670498 85 261
## 4 mod_peche chasse sous-marine 6.1302682 16 261
## 5 mod_peche peche du bord 44.8275862 117 261
## 6 mod_peche peche embarquée 48.2758621 126 261
## 7 mod_peche peche à l'oursin 0.7662835 2 261
## 8 sexe femme 2.6819923 7 261
## 9 sexe homme 97.3180077 254 261
## 10 res_tour occasionnel 9.5785441 25 261
## 11 res_tour resident 78.1609195 204 261
## 12 res_tour secondaire 6.5134100 17 261
## 13 res_tour touriste 5.7471264 15 261
## 14 Temps_peche_estime.cat2h <2h 10.7279693 28 261
## 15 Temps_peche_estime.cat2h >=2h 89.2720307 233 261
## 16 zone.gp Agriates 1.9157088 5 261
## 17 zone.gp Est Cap 43.6781609 114 261
## 18 zone.gp nimp_ou 32.1839080 84 261
## 19 zone.gp Nord Cap 1.9157088 5 261
## 20 zone.gp Ouest Cap 9.5785441 25 261
## 21 zone.gp Saint-Florent 10.7279693 28 261
## 22 age_classe 13-24 1.9230769 5 260
## 23 age_classe 25-39 15.3846154 40 260
## 24 age_classe 40-49 23.4615385 61 260
## 25 age_classe 50-59 44.6153846 116 260
## 26 age_classe 60-69 8.4615385 22 260
## 27 age_classe 70 et plus 6.1538462 16 260
## 28 cat_pro.gp activite 51.5384615 134 260
## 29 cat_pro.gp etudiant 1.5384615 4 260
## 30 cat_pro.gp retraite 37.6923077 98 260
## 31 cat_pro.gp sans_emploi-en_arret 9.2307692 24 260
## 32 nb_sort_an_cat Q1 (<=10) 26.8199234 70 261
## 33 nb_sort_an_cat Q2 (11-15) 30.2681992 79 261
## 34 nb_sort_an_cat Q3 (16-30) 20.3065134 53 261
## 35 nb_sort_an_cat Q4 (>=31) 22.6053640 59 261
## 36 classe_avis_pnm negatif 0.7692308 2 260
## 37 classe_avis_pnm p_avis 15.3846154 40 260
## 38 classe_avis_pnm positif 83.8461538 218 260
## 39 poss_bat non 52.8735632 138 261
## 40 poss_bat oui 47.1264368 123 261
## 41 time.day.gp am 51.5384615 134 260
## 42 time.day.gp journee 3.4615385 9 260
## 43 time.day.gp nimp_q 32.6923077 85 260
## 44 time.day.gp nuit 0.3846154 1 260
## 45 time.day.gp pm 11.9230769 31 260
## 46 dep.mod_peche.chr < 100 euros 36.4341085 94 258
## 47 dep.mod_peche.chr entre 100-500 euros 22.8682171 59 258
## 48 dep.mod_peche.chr entre 1000-2000 euros 9.6899225 25 258
## 49 dep.mod_peche.chr entre 500-1000 euros 11.2403101 29 258
## 50 dep.mod_peche.chr supérieur à 2000 19.7674419 51 258
write.csv2(results_df.1, "Tables/Summary/summary_prop_2020-2022.csv", row.names = F)
df.2 <- filter(df.red, a %in% c("2023"))
df.2[, colSums(is.na(df.2)) != nrow(df.2)]
## a mod_peche sexe res_tour Temps_peche_estime.cat2h
## 1 2023 peche embarquée homme resident >=2h
## 2 2023 peche embarquée homme resident >=2h
## 3 2023 peche embarquée homme resident >=2h
## 4 2023 peche embarquée homme resident >=2h
## 5 2023 peche embarquée homme resident >=2h
## 6 2023 peche embarquée homme resident >=2h
## 7 2023 peche embarquée homme resident >=2h
## 8 2023 peche embarquée homme resident >=2h
## 9 2023 peche embarquée homme resident >=2h
## 10 2023 peche embarquée homme resident >=2h
## 11 2023 peche du bord homme resident >=2h
## 12 2023 peche embarquée homme secondaire >=2h
## 13 2023 peche embarquée femme resident >=2h
## 14 2023 chasse sous-marine femme touriste >=2h
## 15 2023 chasse sous-marine homme touriste >=2h
## 16 2023 peche du bord homme resident >=2h
## 17 2023 peche du bord homme resident >=2h
## 18 2023 chasse sous-marine homme touriste >=2h
## 19 2023 chasse sous-marine homme touriste >=2h
## 20 2023 peche du bord homme resident >=2h
## 21 2023 peche embarquée femme touriste >=2h
## 22 2023 chasse sous-marine homme touriste >=2h
## 23 2023 chasse sous-marine homme resident >=2h
## 24 2023 peche du bord homme occasionnel <2h
## 25 2023 peche du bord homme resident >=2h
## 26 2023 peche du bord homme touriste >=2h
## 27 2023 peche du bord homme resident >=2h
## 28 2023 peche du bord homme resident >=2h
## 29 2023 peche du bord homme resident >=2h
## 30 2023 peche du bord homme touriste >=2h
## 31 2023 peche du bord homme resident >=2h
## 32 2023 chasse sous-marine homme resident <2h
## 33 2023 peche embarquée homme secondaire >=2h
## 34 2023 chasse sous-marine homme secondaire >=2h
## 35 2023 peche du bord homme touriste >=2h
## 36 2023 peche du bord homme touriste >=2h
## 37 2023 peche du bord homme touriste >=2h
## 38 2023 chasse sous-marine homme secondaire >=2h
## 39 2023 peche embarquée homme touriste >=2h
## 40 2023 peche du bord homme touriste >=2h
## 41 2023 peche du bord homme secondaire >=2h
## 42 2023 peche du bord homme resident >=2h
## 43 2023 peche du bord homme resident >=2h
## 44 2023 peche du bord homme resident >=2h
## 45 2023 peche embarquée homme touriste >=2h
## 46 2023 peche du bord homme resident <2h
## 47 2023 peche du bord homme resident <2h
## 48 2023 peche du bord homme resident >=2h
## 49 2023 peche du bord homme touriste >=2h
## 50 2023 peche du bord homme touriste >=2h
## 51 2023 peche embarquée homme resident >=2h
## 52 2023 peche du bord homme touriste <2h
## 53 2023 chasse sous-marine homme resident >=2h
## 54 2023 peche du bord homme resident >=2h
## 55 2023 peche du bord homme resident >=2h
## 56 2023 peche du bord homme touriste >=2h
## 57 2023 peche du bord homme touriste >=2h
## 58 2023 peche du bord homme secondaire >=2h
## 59 2023 chasse sous-marine homme resident >=2h
## 60 2023 chasse sous-marine homme resident <2h
## 61 2023 peche du bord homme resident >=2h
## 62 2023 peche du bord homme resident >=2h
## 63 2023 peche du bord homme touriste >=2h
## 64 2023 peche du bord homme resident >=2h
## 65 2023 chasse sous-marine homme resident >=2h
## 66 2023 peche du bord homme touriste >=2h
## 67 2023 peche du bord femme secondaire >=2h
## 68 2023 chasse sous-marine homme secondaire <2h
## 69 2023 peche du bord homme touriste <2h
## 70 2023 chasse sous-marine homme touriste <2h
## 71 2023 peche du bord homme touriste >=2h
## 72 2023 chasse sous-marine homme resident >=2h
## 73 2023 peche du bord homme touriste <2h
## 74 2023 peche du bord homme touriste >=2h
## 75 2023 peche du bord homme touriste <2h
## 76 2023 peche du bord homme touriste <2h
## 77 2023 peche du bord homme resident >=2h
## 78 2023 peche du bord homme touriste >=2h
## 79 2023 chasse sous-marine homme touriste <2h
## 80 2023 peche du bord homme touriste >=2h
## 81 2023 peche du bord homme touriste >=2h
## 82 2023 peche du bord homme resident <2h
## 83 2023 peche du bord homme touriste >=2h
## 84 2023 peche du bord homme resident >=2h
## 85 2023 chasse sous-marine homme touriste >=2h
## 86 2023 peche du bord homme resident >=2h
## 87 2023 peche embarquée homme resident >=2h
## 88 2023 peche du bord homme resident >=2h
## 89 2023 peche du bord homme resident <2h
## 90 2023 peche du bord homme resident >=2h
## 91 2023 peche du bord homme resident >=2h
## 92 2023 peche du bord homme resident >=2h
## 93 2023 peche du bord homme resident <2h
## 94 2023 peche du bord homme resident >=2h
## 95 2023 peche du bord homme resident >=2h
## 96 2023 peche du bord homme resident >=2h
## 97 2023 peche du bord homme resident >=2h
## 98 2023 peche embarquée homme resident >=2h
## 99 2023 peche du bord homme resident >=2h
## 100 2023 peche du bord homme resident >=2h
## 101 2023 peche du bord homme resident >=2h
## 102 2023 peche embarquée homme resident >=2h
## 103 2023 chasse sous-marine femme resident >=2h
## 104 2023 peche du bord homme touriste >=2h
## 105 2023 peche du bord homme resident >=2h
## 106 2023 peche du bord homme resident >=2h
## 107 2023 peche du bord homme resident >=2h
## 108 2023 peche du bord femme touriste >=2h
## 109 2023 peche du bord homme touriste <2h
## 110 2023 peche du bord homme touriste >=2h
## 111 2023 peche du bord homme resident >=2h
## 112 2023 peche du bord homme touriste >=2h
## 113 2023 peche du bord homme touriste >=2h
## 114 2023 peche du bord homme resident >=2h
## 115 2023 peche du bord homme resident >=2h
## 116 2023 peche du bord homme touriste >=2h
## 117 2023 peche du bord homme touriste >=2h
## 118 2023 peche du bord homme touriste >=2h
## 119 2023 peche du bord homme touriste >=2h
## 120 2023 peche du bord homme touriste <2h
## 121 2023 peche du bord homme touriste >=2h
## 122 2023 peche du bord homme touriste >=2h
## 123 2023 peche du bord homme resident >=2h
## 124 2023 peche du bord homme resident >=2h
## 125 2023 peche du bord homme resident >=2h
## 126 2023 peche du bord homme resident >=2h
## 127 2023 peche du bord homme resident >=2h
## 128 2023 chasse sous-marine homme resident <2h
## 129 2023 peche du bord homme resident <2h
## 130 2023 peche du bord femme resident >=2h
## 131 2023 peche du bord homme resident >=2h
## 132 2023 peche du bord homme resident >=2h
## 133 2023 peche du bord homme resident >=2h
## 134 2023 peche du bord homme resident >=2h
## 135 2023 peche du bord homme resident <2h
## 136 2023 peche du bord homme resident >=2h
## 137 2023 peche du bord homme resident >=2h
## 138 2023 peche du bord homme resident >=2h
## 139 2023 peche du bord homme resident >=2h
## 140 2023 peche du bord homme touriste >=2h
## 141 2023 peche du bord homme resident >=2h
## 142 2023 peche du bord homme resident >=2h
## 143 2023 chasse sous-marine homme resident >=2h
## 144 2023 peche du bord homme resident >=2h
## 145 2023 peche du bord homme resident >=2h
## 146 2023 peche du bord homme resident >=2h
## 147 2023 peche du bord homme resident >=2h
## 148 2023 peche du bord homme resident >=2h
## 149 2023 peche du bord homme resident >=2h
## 150 2023 peche du bord homme resident >=2h
## 151 2023 peche du bord homme resident >=2h
## 152 2023 peche du bord homme resident >=2h
## 153 2023 peche du bord femme resident >=2h
## 154 2023 peche du bord homme resident <2h
## 155 2023 peche du bord homme resident <2h
## 156 2023 peche du bord homme resident >=2h
## 157 2023 peche du bord homme resident >=2h
## 158 2023 peche du bord homme resident >=2h
## 159 2023 peche du bord homme resident >=2h
## 160 2023 peche du bord homme resident >=2h
## 161 2023 peche du bord homme resident >=2h
## 162 2023 peche du bord homme resident >=2h
## 163 2023 peche du bord homme resident >=2h
## 164 2023 peche du bord homme resident >=2h
## 165 2023 peche du bord homme resident >=2h
## 166 2023 peche du bord homme resident >=2h
## 167 2023 peche du bord homme resident >=2h
## 168 2023 peche du bord homme resident <2h
## 169 2023 peche du bord homme resident >=2h
## 170 2023 peche du bord homme resident >=2h
## 171 2023 peche du bord homme resident >=2h
## 172 2023 peche du bord homme resident >=2h
## zone.gp
## 1 nimp_ou
## 2 nimp_ou
## 3 <NA>
## 4 nimp_ou
## 5 nimp_ou
## 6 Est Cap
## 7 nimp_ou
## 8 nimp_ou
## 9 nimp_ou
## 10 Agriates
## 11 Est Cap
## 12 nimp_ou
## 13 nimp_ou
## 14 nimp_ou
## 15 nimp_ou
## 16 nimp_ou
## 17 Est Cap
## 18 Est Cap
## 19 Est Cap
## 20 Est Cap
## 21 nimp_ou
## 22 nimp_ou
## 23 nimp_ou
## 24 nimp_ou
## 25 Est Cap
## 26 Est Cap
## 27 Est Cap
## 28 nimp_ou
## 29 Est Cap
## 30 nimp_ou
## 31 nimp_ou
## 32 Est Cap
## 33 nimp_ou
## 34 nimp_ou
## 35 Est Cap
## 36 Est Cap
## 37 Est Cap
## 38 Est Cap
## 39 nimp_ou
## 40 Est Cap
## 41 nimp_ou
## 42 Est Cap
## 43 Est Cap
## 44 Est Cap
## 45 Est Cap
## 46 Est Cap
## 47 Est Cap
## 48 nimp_ou
## 49 Est Cap
## 50 Saint-Florent
## 51 nimp_ou
## 52 Est Cap
## 53 Est Cap
## 54 nimp_ou
## 55 Est Cap
## 56 Est Cap
## 57 Est Cap
## 58 Est Cap
## 59 Est Cap
## 60 Est Cap
## 61 nimp_ou
## 62 Ouest Cap
## 63 Ouest Cap
## 64 Est Cap
## 65 nimp_ou
## 66 nimp_ou
## 67 Est Cap
## 68 Est Cap
## 69 Est Cap
## 70 Est Cap
## 71 Est Cap
## 72 nimp_ou
## 73 Est Cap
## 74 Est Cap
## 75 Est Cap
## 76 Est Cap
## 77 Est Cap
## 78 Est Cap
## 79 Est Cap
## 80 Est Cap
## 81 Est Cap
## 82 Est Cap
## 83 nimp_ou
## 84 nimp_ou
## 85 Nord Cap
## 86 nimp_ou
## 87 Est Cap
## 88 nimp_ou
## 89 Est Cap
## 90 nimp_ou
## 91 Saint-Florent
## 92 Est Cap
## 93 Est Cap
## 94 nimp_ou
## 95 Est Cap
## 96 nimp_ou
## 97 Est Cap
## 98 Est Cap
## 99 Est Cap
## 100 nimp_ou
## 101 Est Cap
## 102 nimp_ou
## 103 nimp_ou
## 104 Est Cap
## 105 nimp_ou
## 106 Est Cap
## 107 Est Cap
## 108 Est Cap
## 109 Ouest Cap
## 110 nimp_ou
## 111 Est Cap
## 112 nimp_ou
## 113 nimp_ou
## 114 nimp_ou
## 115 Est Cap
## 116 Saint-Florent
## 117 Saint-Florent
## 118 Saint-Florent
## 119 Saint-Florent
## 120 Saint-Florent
## 121 nimp_ou
## 122 Saint-Florent
## 123 Saint-Florent
## 124 nimp_ou
## 125 nimp_ou
## 126 Est Cap
## 127 Est Cap
## 128 Est Cap
## 129 nimp_ou
## 130 Est Cap
## 131 Est Cap
## 132 nimp_ou
## 133 nimp_ou
## 134 Est Cap
## 135 Est Cap
## 136 nimp_ou
## 137 nimp_ou
## 138 Saint-Florent
## 139 nimp_ou
## 140 Saint-Florent
## 141 Est Cap
## 142 nimp_ou
## 143 nimp_ou
## 144 Est Cap
## 145 Saint-Florent
## 146 Est Cap
## 147 Est Cap
## 148 Est Cap
## 149 Est Cap
## 150 nimp_ou
## 151 nimp_ou
## 152 nimp_ou
## 153 Saint-Florent
## 154 nimp_ou
## 155 Saint-Florent
## 156 Saint-Florent
## 157 nimp_ou
## 158 Est Cap
## 159 nimp_ou
## 160 Est Cap
## 161 Saint-Florent
## 162 Saint-Florent
## 163 Saint-Florent
## 164 nimp_ou
## 165 nimp_ou
## 166 nimp_ou
## 167 Est Cap
## 168 Est Cap
## 169 nimp_ou
## 170 Saint-Florent
## 171 nimp_ou
## 172 nimp_ou
df.2 <- droplevels(df.2)
percentage_results <- sapply(df.2, calculate_percentages)
occurence_results <- sapply(df.2, calculate_occurences)
#saveRDS(percentage_results, "percentage_results.rds") #for ChatGPT
# Display the results
print(percentage_results)
## $a
## df.red
## 2023
## 100
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée
## 12.20930 76.16279 11.62791
##
## $sexe
## df.red
## femme homme
## 4.651163 95.348837
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 0.5813953 66.8604651 4.6511628 27.9069767
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 13.95349 86.04651
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 0.5847953 46.1988304 39.7660819 0.5847953 1.7543860
## Saint-Florent
## 11.1111111
##
## $age_classe
## numeric(0)
##
## $cat_pro.gp
## numeric(0)
##
## $nb_sort_an_cat
## numeric(0)
##
## $classe_avis_pnm
## numeric(0)
##
## $poss_bat
## numeric(0)
##
## $time.day.gp
## numeric(0)
##
## $dep.mod_peche.chr
## numeric(0)
results_perc <- do.call(rbind, lapply(percentage_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
print(occurence_results)
## $a
## df.red
## 2023
## 172
##
## $mod_peche
## df.red
## chasse sous-marine peche du bord peche embarquée
## 21 131 20
##
## $sexe
## df.red
## femme homme
## 8 164
##
## $res_tour
## df.red
## occasionnel resident secondaire touriste
## 1 115 8 48
##
## $Temps_peche_estime.cat2h
## df.red
## <2h >=2h
## 24 148
##
## $zone.gp
## df.red
## Agriates Est Cap nimp_ou Nord Cap Ouest Cap
## 1 79 68 1 3
## Saint-Florent
## 19
##
## $age_classe
## < table of extent 0 >
##
## $cat_pro.gp
## < table of extent 0 >
##
## $nb_sort_an_cat
## < table of extent 0 >
##
## $classe_avis_pnm
## < table of extent 0 >
##
## $poss_bat
## < table of extent 0 >
##
## $time.day.gp
## < table of extent 0 >
##
## $dep.mod_peche.chr
## < table of extent 0 >
results_occ <- do.call(rbind, lapply(occurence_results, function(x) {
if(is.matrix(x)) as.data.frame(x) else as.data.frame(t(x))
}))
results_df.2 <- bind_cols(results_perc, results_occ)
## New names:
## • `Var1` -> `Var1...1`
## • `df.red` -> `df.red...2`
## • `Freq` -> `Freq...3`
## • `Var1` -> `Var1...4`
## • `df.red` -> `df.red...5`
## • `Freq` -> `Freq...6`
setdiff(results_df.2$df.2red...2, results_df.2$df.2red...5)
## NULL
results_df.2 <- results_df.2[, c(1,2,3,6)]
results_df.2$Var1...1 <- rownames(results_df.2)
results_df.2$Var1...1 <- str_sub(results_df.2$Var1, end=-3)
names(results_df.2)[names(results_df.2) == "Var1...1"] <- "parametre"
names(results_df.2)[names(results_df.2) == "df.red...2"] <- "categorie"
names(results_df.2)[names(results_df.2) == "Freq...3"] <- "pourcentage"
names(results_df.2)[names(results_df.2) == "Freq...6"] <- "n"
results_df.2$parametre <- ifelse(results_df.2$categorie == "2023", "a", results_df.2$parametre)
results_df.2 %>% group_by(parametre) %>% summarise(N = sum(n, na.rm = T)) -> N
results_df.2 <- left_join(results_df.2, N)
## Joining with `by = join_by(parametre)`
results_df.2
## parametre categorie pourcentage n N
## 1 a 2023 100.0000000 172 172
## 2 mod_peche chasse sous-marine 12.2093023 21 172
## 3 mod_peche peche du bord 76.1627907 131 172
## 4 mod_peche peche embarquée 11.6279070 20 172
## 5 sexe femme 4.6511628 8 172
## 6 sexe homme 95.3488372 164 172
## 7 res_tour occasionnel 0.5813953 1 172
## 8 res_tour resident 66.8604651 115 172
## 9 res_tour secondaire 4.6511628 8 172
## 10 res_tour touriste 27.9069767 48 172
## 11 Temps_peche_estime.cat2h <2h 13.9534884 24 172
## 12 Temps_peche_estime.cat2h >=2h 86.0465116 148 172
## 13 zone.gp Agriates 0.5847953 1 171
## 14 zone.gp Est Cap 46.1988304 79 171
## 15 zone.gp nimp_ou 39.7660819 68 171
## 16 zone.gp Nord Cap 0.5847953 1 171
## 17 zone.gp Ouest Cap 1.7543860 3 171
## 18 zone.gp Saint-Florent 11.1111111 19 171
write.csv2(results_df.2, "Tables/Summary/summary_prop_2023.csv", row.names = F)
unique(results_df$parametre)
## [1] "a" "mod_peche"
## [3] "sexe" "res_tour"
## [5] "Temps_peche_estime.cat2h" "zone.gp"
## [7] "age_classe" "cat_pro.gp"
## [9] "nb_sort_an_cat" "classe_avis_pnm"
## [11] "poss_bat" "time.day.gp"
## [13] "dep.mod_peche.chr"
results_df %>% filter(parametre == "zone.gp") -> df.plot
ggplot(df.plot, aes(x="", y=pourcentage, fill=categorie)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle("Secteurs de pêches préférés 2020-2023") +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(pourcentage/100)), position = position_stack(vjust = 0.55)) # Ajouter les pourcentages
ggsave("Figs/Secteurs/secteurs_2020-2023.png", width = 7, height = 7)
results_df.1 %>% filter(parametre == "zone.gp") -> df.plot
ggplot(df.plot, aes(x="", y=pourcentage, fill=categorie)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle("Secteurs de pêches préférés 2020-2022") +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(pourcentage/100)), position = position_stack(vjust = 0.55)) # Ajouter les pourcentages
ggsave("Figs/Secteurs/secteurs_2020-2022.png", width = 7, height = 7)
results_df.2 %>% filter(parametre == "zone.gp") -> df.plot
ggplot(df.plot, aes(x="", y=pourcentage, fill=categorie)) +
geom_bar(stat="identity", width=1) +
coord_polar(theta = "y", start=0) +
ggtitle("Secteurs de pêches préférés 2023") +
theme_bw() +
theme(#axis.line=element_blank(),
#axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
#legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
#panel.grid.major=element_blank(),
#panel.grid.minor=element_blank(),
#plot.background=element_blank()
) +
theme(plot.title = element_text(hjust = 0.5)) +
geom_text(aes(label = scales::percent(pourcentage/100)), position = position_stack(vjust = 0.55)) # Ajouter les pourcentages
ggsave("Figs/Secteurs/secteurs_2023.png", width = 7, height = 7)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red", "results_df", "results_df.1", "results_df.2")))
# plot species targeted ####
survey$espcib1
## [1] "NA" "NA"
## [3] "NA" "NA"
## [5] "NA" "NA"
## [7] "NA" "NA"
## [9] "NA" "NA"
## [11] "NA" "NA"
## [13] "NA" "NA"
## [15] "NA" "NA"
## [17] "NA" "NA"
## [19] "NA" "NA"
## [21] "NA" "NA"
## [23] "NA" "NA"
## [25] "NA" "NA"
## [27] "NA" "NA"
## [29] "NA" "NA"
## [31] "NA" "NA"
## [33] "NA" "NA"
## [35] "NA" "NA"
## [37] "NA" "NA"
## [39] "NA" "NA"
## [41] "NA" "NA"
## [43] "NA" "NA"
## [45] "NA" "NA"
## [47] "NA" "NA"
## [49] "NA" "NA"
## [51] "NA" "NA"
## [53] "NA" "NA"
## [55] "NA" "NA"
## [57] "NA" "NA"
## [59] "NA" "NA"
## [61] "NA" "NA"
## [63] "NA" "NA"
## [65] "NA" "NA"
## [67] "NA" "NA"
## [69] "NA" "NA"
## [71] "NA" "NA"
## [73] "NA" "NA"
## [75] "NA" "NA"
## [77] "NA" "NA"
## [79] "NA" "NA"
## [81] "NA" "NA"
## [83] "NA" "NA"
## [85] "NA" "NA"
## [87] "NA" "NA"
## [89] "NA" "NA"
## [91] "NA" "NA"
## [93] "NA" "NA"
## [95] "NA" "NA"
## [97] "NA" "NA"
## [99] "NA" "NA"
## [101] "NA" "NA"
## [103] "NA" "NA"
## [105] "NA" "NA"
## [107] "NA" "NA"
## [109] "NA" "NA"
## [111] "NA" "NA"
## [113] "NA" "NA"
## [115] "NA" "NA"
## [117] "NA" "NA"
## [119] "NA" "NA"
## [121] "NA" "NA"
## [123] "NA" "NA"
## [125] "NA" "NA"
## [127] "NA" "NA"
## [129] "NA" "NA"
## [131] "NA" "NA"
## [133] "NA" "NA"
## [135] "NA" "NA"
## [137] "NA" "NA"
## [139] "NA" "NA"
## [141] "NA" "NA"
## [143] "NA" "NA"
## [145] "NA" "NA"
## [147] "NA" "NA"
## [149] "NA" "NA"
## [151] "NA" "NA"
## [153] "NA" "NA"
## [155] "NA" "NA"
## [157] "NA" "NA"
## [159] "NA" "NA"
## [161] "NA" "NA"
## [163] "NA" "NA"
## [165] "NA" "NA"
## [167] "NA" "Dentex dentex"
## [169] "Dentex dentex" "Dentex dentex"
## [171] "Sparus aurata" "Dentex dentex"
## [173] "Pagellus erythrinus erythrinus" "Dentex dentex"
## [175] "Spondyliosoma cantharus" "toutes"
## [177] "toutes" "toutes"
## [179] "Pagellus erythrinus" "Sparus aurata"
## [181] "Diplodus sargus" "toutes"
## [183] "Serranus cabrilla" "Dentex dentex"
## [185] "Sparus aurata" "toutes"
## [187] "Dentex dentex" "toutes"
## [189] "Dicentrarchus labrax" "Pagrus pagrus"
## [191] "Dentex dentex" "Serranus cabrilla"
## [193] "Oblada melanura" "toutes"
## [195] "Pagrus pagrus" "Dentex dentex"
## [197] "Sphyraena barracuda" "Sarpa salpa"
## [199] "Sparus aurata" "Dentex dentex"
## [201] "Dentex dentex" "toutes"
## [203] "Carnassiers" "toutes"
## [205] "Sarpa salpa" "toutes"
## [207] "toutes" "toutes"
## [209] "Sepia officinalis" "Sparus aurata"
## [211] "Sparus aurata" "toutes"
## [213] "toutes" "toutes"
## [215] "toutes" "toutes"
## [217] "Dentex dentex" "toutes"
## [219] "soupe" "Dentex dentex"
## [221] "toutes" "NA"
## [223] "Dentex dentex" "Serranus cabrilla"
## [225] "Pagellus erythrinus erythrinus" "NA"
## [227] "Diplodus vulgaris" "Dentex dentex"
## [229] "Dicentrarchus labrax" "Dicentrarchus labrax"
## [231] "Dentex dentex" "Serranus cabrilla"
## [233] "Pagellus erythrinus erythrinus" "Pagellus erythrinus erythrinus"
## [235] "Pagellus erythrinus erythrinus" "Pagellus erythrinus erythrinus"
## [237] "Maquereau" "Serranus scriba"
## [239] "Sparus aurata" "Serranus cabrilla"
## [241] "Pagrus pagrus" "Pagrus pagrus"
## [243] "Dentex dentex" "Serranus scriba"
## [245] "Dentex dentex" "Serranus cabrilla"
## [247] "Coris julis" "Loligo vulgaris"
## [249] "Richolas" "Dentex dentex"
## [251] "Dentex dentex" "Dentex dentex"
## [253] "Serranus cabrilla" "Serranus cabrilla"
## [255] "Dentex dentex" "Serranus scriba"
## [257] "Dentex dentex" "Pagrus pagrus"
## [259] "Pagrus pagrus" "Encornet"
## [261] "Dentex dentex" "NA"
## [263] "NA" "NA"
## [265] "NA" "NA"
## [267] "NA" "NA"
## [269] "NA" "NA"
## [271] "NA" "NA"
## [273] "NA" "NA"
## [275] "NA" "NA"
## [277] "NA" "NA"
## [279] "NA" "NA"
## [281] "NA" "NA"
## [283] "NA" "NA"
## [285] "NA" "NA"
## [287] "NA" "NA"
## [289] "NA" "NA"
## [291] "NA" "NA"
## [293] "NA" "NA"
## [295] "NA" "NA"
## [297] "NA" "NA"
## [299] "NA" "NA"
## [301] "NA" "NA"
## [303] "NA" "NA"
## [305] "NA" "NA"
## [307] "NA" "NA"
## [309] "NA" "NA"
## [311] "NA" "NA"
## [313] "NA" "NA"
## [315] "NA" "NA"
## [317] "NA" "NA"
## [319] "NA" "NA"
## [321] "NA" "NA"
## [323] "NA" "NA"
## [325] "NA" "NA"
## [327] "NA" "NA"
## [329] "NA" "NA"
## [331] "NA" "NA"
## [333] "NA" "NA"
## [335] "NA" "NA"
## [337] "NA" "NA"
## [339] "NA" "NA"
## [341] "NA" "NA"
## [343] "NA" "NA"
## [345] "NA" "NA"
## [347] "NA" "NA"
## [349] "NA" "Sparus aurata"
## [351] "Dentex dentex" "Dentex dentex"
## [353] "NA" "NA"
## [355] "Dentex dentex" "NA"
## [357] "NA" "NA"
## [359] "NA" "NA"
## [361] "Dentex dentex" "Dentex dentex"
## [363] "NA" "NA"
## [365] "NA" "Dentex dentex"
## [367] "NA" "NA"
## [369] "NA" "Dentex dentex"
## [371] "NA" "NA"
## [373] "NA" "NA"
## [375] "NA" "NA"
## [377] "Dentex dentex" "Dentex dentex"
## [379] "NA" "NA"
## [381] "Sparus aurata" "Sparus aurata"
## [383] "Sparus aurata" "Sparus aurata"
## [385] "NA" "NA"
## [387] "Sparus aurata" "Sparus aurata"
## [389] "Oblada melanura" "Oblada melanura"
## [391] "Serranus scriba" "NA"
## [393] "NA" "NA"
## [395] "NA" "NA"
## [397] "Oblada melanura" "NA"
## [399] "Sparus aurata" "NA"
## [401] "Dicentrarchus labrax" "Dentex dentex"
## [403] "NA" "NA"
## [405] "NA" "NA"
## [407] "NA" "NA"
## [409] "NA" "NA"
## [411] "NA" "NA"
## [413] "NA" "Sparus aurata"
## [415] "Sparus aurata" "Sparus aurata"
## [417] "Sparus aurata" "Sparus aurata"
## [419] "Dicentrarchus labrax" "NA"
## [421] "NA" "NA"
## [423] "NA" "NA"
## [425] "NA" "NA"
## [427] "NA" "NA"
## [429] "NA" "NA"
## [431] "NA" "NA"
## [433] "NA" "NA"
## [435] "NA" "NA"
## [437] "NA" "NA"
## [439] "NA" "NA"
## [441] "NA" "NA"
## [443] "NA" "NA"
## [445] "NA" "NA"
## [447] "NA" "Diplodus sargus"
## [449] "NA" "Sparus aurata"
## [451] "NA" "NA"
## [453] "NA" "NA"
## [455] "NA" "NA"
## [457] "NA" "NA"
## [459] "NA" "NA"
## [461] "NA" "NA"
## [463] "NA" "NA"
## [465] "NA" "NA"
## [467] "NA" "NA"
## [469] "NA" "Dentex dentex"
## [471] "NA" "Sphyraena barracuda"
## [473] "Dentex dentex" "NA"
## [475] "NA" "NA"
## [477] "NA" "Sphyraena barracuda"
## [479] "Diplodus sargus" "roche"
## [481] "roche" "NA"
## [483] "toutes" "toutes"
## [485] "roches" "Sphyraena barracuda"
## [487] "roches" "sable"
## [489] "roche" "toutes"
## [491] "roches" "sable"
## [493] "toutes" "sable"
## [495] "sable" "sable"
## [497] "toutes" "toutes"
## [499] "sable" "roche"
## [501] "roche" "roche"
## [503] "sable" "sable"
## [505] "sable" "toutes"
## [507] "toutes" "sable"
## [509] "sable" "toutes"
## [511] "sable" "sable"
## [513] "NA" "sparides"
## [515] "NA" "Sparus aurata"
## [517] "soupe" "soupe"
## [519] "soupe" NA
## [521] NA NA
## [523] NA NA
## [525] NA NA
## [527] NA NA
## [529] NA NA
## [531] NA NA
## [533] NA NA
## [535] NA NA
## [537] NA NA
## [539] NA NA
## [541] NA NA
## [543] NA NA
## [545] NA NA
## [547] NA NA
## [549] NA NA
## [551] NA NA
## [553] NA NA
## [555] NA NA
## [557] NA NA
## [559] NA NA
## [561] NA NA
## [563] NA NA
## [565] NA NA
## [567] NA NA
## [569] NA NA
## [571] NA NA
## [573] NA NA
## [575] NA NA
## [577] NA NA
## [579] NA NA
## [581] NA NA
## [583] NA NA
## [585] NA NA
## [587] NA NA
## [589] NA NA
## [591] NA NA
## [593] NA NA
## [595] NA NA
## [597] NA NA
## [599] NA NA
## [601] NA NA
## [603] NA NA
## [605] NA NA
## [607] NA NA
## [609] NA NA
## [611] NA NA
## [613] NA NA
## [615] NA NA
## [617] NA NA
## [619] NA NA
## [621] NA NA
## [623] NA NA
## [625] NA NA
## [627] NA NA
## [629] NA NA
## [631] NA NA
## [633] NA NA
## [635] NA NA
## [637] NA NA
## [639] NA NA
## [641] NA NA
## [643] NA NA
## [645] NA NA
## [647] NA NA
## [649] NA NA
## [651] NA NA
## [653] NA NA
## [655] NA NA
## [657] NA NA
## [659] NA NA
## [661] NA NA
## [663] NA NA
## [665] NA NA
## [667] NA NA
## [669] NA NA
## [671] NA NA
## [673] NA NA
## [675] NA NA
## [677] NA NA
## [679] NA NA
## [681] NA NA
## [683] NA NA
## [685] NA NA
## [687] NA NA
## [689] NA NA
## [691] NA NA
## [693] NA NA
## [695] NA NA
## [697] NA NA
## [699] "Loligo vulgaris" "Dentex dentex"
## [701] "Pagellus erythrinus erythrinus" "Pagrus pagrus"
## [703] "NA" "Dentex dentex"
## [705] "Pagellus erythrinus erythrinus" "Dentex dentex"
## [707] "Pagrus pagrus" "Serranus cabrilla"
## [709] "Diplodus sargus" "NA"
## [711] "Dentex dentex" "Diplodus sargus"
## [713] "Loligo vulgaris" "Dentex dentex"
## [715] "Thunnus thynnus" "Diplodus sargus"
## [717] "NA" "Coris julis"
## [719] "Loligo vulgaris" "Diplodus sargus"
## [721] "Pelagides" "NA"
## [723] "NA" "Dentex dentex"
## [725] "Dentex dentex" "Dentex dentex"
## [727] "soupe" "Serranus cabrilla"
## [729] "Serranus cabrilla" "Serranus cabrilla"
## [731] "Serranus cabrilla" "Diplodus sargus"
## [733] "Dentex dentex" "NA"
## [735] "Serranus cabrilla" "Serranus cabrilla"
## [737] "NA" "Paracentrotus lividus"
## [739] "Dentex dentex" "Diplodus sargus"
## [741] "Loligo vulgaris" "Dentex dentex"
## [743] "Diplodus sargus" "Dentex dentex"
## [745] "Dentex dentex" "Dentex dentex"
## [747] "NA" "Diplodus sargus"
## [749] "Diplodus sargus" "Dentex dentex"
## [751] "Diplodus sargus" "Serranus cabrilla"
## [753] "Seriola dumerilli" "Mullus ssp"
## [755] "Dentex dentex" "Diplodus sargus"
## [757] "Diplodus sargus" "Sparus aurata"
## [759] "NA" "Diplodus sargus"
## [761] "Pagrus pagrus" "Seriola dumerilli"
## [763] "Diplodus sargus" "Sphyraena barracuda"
## [765] "Dentex dentex" "Diplodus sargus"
## [767] "Sparus aurata" "Diplodus sargus"
## [769] "Diplodus sargus" "Diplodus sargus"
table(survey$espcib1)
##
## Carnassiers Coris julis
## 1 2
## Dentex dentex Dicentrarchus labrax
## 53 5
## Diplodus sargus Diplodus vulgaris
## 21 1
## Encornet Loligo vulgaris
## 1 5
## Maquereau Mullus ssp
## 1 1
## NA Oblada melanura
## 363 4
## Pagellus erythrinus Pagellus erythrinus erythrinus
## 1 8
## Pagrus pagrus Paracentrotus lividus
## 9 1
## Pelagides Richolas
## 1 1
## roche roches
## 6 3
## sable Sarpa salpa
## 13 2
## Sepia officinalis Seriola dumerilli
## 1 2
## Serranus cabrilla Serranus scriba
## 16 4
## soupe sparides
## 5 1
## Sparus aurata Sphyraena barracuda
## 24 5
## Spondyliosoma cantharus Thunnus thynnus
## 1 1
## toutes
## 28
survey$espcib2
## [1] "NA" "NA"
## [3] "NA" "NA"
## [5] "NA" "NA"
## [7] "NA" "NA"
## [9] "NA" "NA"
## [11] "NA" "NA"
## [13] "NA" "NA"
## [15] "NA" "NA"
## [17] "NA" "NA"
## [19] "NA" "NA"
## [21] "NA" "NA"
## [23] "NA" "NA"
## [25] "NA" "NA"
## [27] "NA" "NA"
## [29] "NA" "NA"
## [31] "NA" "NA"
## [33] "NA" "NA"
## [35] "NA" "NA"
## [37] "NA" "NA"
## [39] "NA" "NA"
## [41] "NA" "NA"
## [43] "NA" "NA"
## [45] "NA" "NA"
## [47] "NA" "NA"
## [49] "NA" "NA"
## [51] "NA" "NA"
## [53] "NA" "NA"
## [55] "NA" "NA"
## [57] "NA" "NA"
## [59] "NA" "NA"
## [61] "NA" "NA"
## [63] "NA" "NA"
## [65] "NA" "NA"
## [67] "NA" "NA"
## [69] "NA" "NA"
## [71] "NA" "NA"
## [73] "NA" "NA"
## [75] "NA" "NA"
## [77] "NA" "NA"
## [79] "NA" "NA"
## [81] "NA" "NA"
## [83] "NA" "NA"
## [85] "NA" "NA"
## [87] "NA" "NA"
## [89] "NA" "NA"
## [91] "NA" "NA"
## [93] "NA" "NA"
## [95] "NA" "NA"
## [97] "NA" "NA"
## [99] "NA" "NA"
## [101] "NA" "NA"
## [103] "NA" "NA"
## [105] "NA" "NA"
## [107] "NA" "NA"
## [109] "NA" "NA"
## [111] "NA" "NA"
## [113] "NA" "NA"
## [115] "NA" "NA"
## [117] "NA" "NA"
## [119] "NA" "NA"
## [121] "NA" "NA"
## [123] "NA" "NA"
## [125] "NA" "NA"
## [127] "NA" "NA"
## [129] "NA" "NA"
## [131] "NA" "NA"
## [133] "NA" "NA"
## [135] "NA" "NA"
## [137] "NA" "NA"
## [139] "NA" "NA"
## [141] "NA" "NA"
## [143] "NA" "NA"
## [145] "NA" "NA"
## [147] "NA" "NA"
## [149] "NA" "NA"
## [151] "NA" "NA"
## [153] "NA" "NA"
## [155] "NA" "NA"
## [157] "NA" "NA"
## [159] "NA" "NA"
## [161] "NA" "NA"
## [163] "NA" "NA"
## [165] "NA" "NA"
## [167] "NA" "Sparus aurata"
## [169] "Dicentrarchus labrax" "NA"
## [171] "Dentex dentex" "Dicentrarchus labrax"
## [173] "Scorpaena scrofa" "Loligo vulgaris"
## [175] "Pagrus pagrus" "NA"
## [177] "NA" "NA"
## [179] "Serranus cabrilla" "Diplodus sargus"
## [181] "Oblada melanura" "NA"
## [183] "Pagellus erythrinus" "Lichia amia"
## [185] "NA" "NA"
## [187] "soupe" "NA"
## [189] "Dentex dentex" "Dicentrarchus labrax"
## [191] "Scorpaena scrofa" "Pagellus erythrinus"
## [193] "Diplodus vulgaris" "NA"
## [195] "Spondyliosoma cantharus" "Seriola dumerilli"
## [197] "Dicentrarchus labrax" "Diplodus vulgaris"
## [199] "Diplodus vulgaris" "Pagellus erythrinus"
## [201] "Pagrus pagrus" "Pagellus erythrinus"
## [203] "Sparidae" "NA"
## [205] "Coris julis" "NA"
## [207] "NA" "NA"
## [209] "Sparus aurata" "Dicentrarchus labrax"
## [211] "Dicentrarchus labrax" "NA"
## [213] "NA" "NA"
## [215] "NA" "NA"
## [217] "Sparus aurata" "NA"
## [219] "toutes" "Seriola dumerilli"
## [221] "NA" "NA"
## [223] "Seriola dumerilli" "Coris julis"
## [225] "Pagrus pagrus" "NA"
## [227] "Lichia amia" "Seriola dumerilli"
## [229] "Dentex dentex" "Sparus aurata"
## [231] "Seriola dumerilli" "Pagellus erythrinus"
## [233] "Sarpa salpa" "Sarpa salpa"
## [235] "Serranus cabrilla" "NA"
## [237] "Sarda sarda" "Serranus cabrilla"
## [239] "Serranus cabrilla" "Coris julis"
## [241] "Dentex dentex" "Dentex dentex"
## [243] "Vive" "Serranus cabrilla"
## [245] "Pagrus pagrus" "Coris julis"
## [247] "Serranus scriba" "Pagrus pagrus"
## [249] "Dentex dentex" "Seriola dumerilli"
## [251] "Trachinotus ovatus" "Seriola dumerilli"
## [253] "Serranus scriba" "Serranus scriba"
## [255] "Diplodus sargus" "Coris julis"
## [257] "Richolu" "Dentex dentex"
## [259] "Dentex dentex" "Dentex dentex"
## [261] "NA" "NA"
## [263] "NA" "NA"
## [265] "NA" "NA"
## [267] "NA" "NA"
## [269] "NA" "NA"
## [271] "NA" "NA"
## [273] "NA" "NA"
## [275] "NA" "NA"
## [277] "NA" "NA"
## [279] "NA" "NA"
## [281] "NA" "NA"
## [283] "NA" "NA"
## [285] "NA" "NA"
## [287] "NA" "NA"
## [289] "NA" "NA"
## [291] "NA" "NA"
## [293] "NA" "NA"
## [295] "NA" "NA"
## [297] "NA" "NA"
## [299] "NA" "NA"
## [301] "NA" "NA"
## [303] "NA" "NA"
## [305] "NA" "NA"
## [307] "NA" "NA"
## [309] "NA" "NA"
## [311] "NA" "NA"
## [313] "NA" "NA"
## [315] "NA" "NA"
## [317] "NA" "NA"
## [319] "NA" "NA"
## [321] "NA" "NA"
## [323] "NA" "NA"
## [325] "NA" "NA"
## [327] "NA" "NA"
## [329] "NA" "NA"
## [331] "NA" "NA"
## [333] "NA" "NA"
## [335] "NA" "NA"
## [337] "NA" "NA"
## [339] "NA" "NA"
## [341] "NA" "NA"
## [343] "NA" "NA"
## [345] "NA" "NA"
## [347] "NA" "NA"
## [349] "NA" "Diplodus sargus"
## [351] "NA" "NA"
## [353] "NA" "NA"
## [355] "NA" "NA"
## [357] "NA" "NA"
## [359] "NA" "NA"
## [361] "NA" "Sparus aurata"
## [363] "NA" "NA"
## [365] "NA" "NA"
## [367] "NA" "NA"
## [369] "NA" "NA"
## [371] "NA" "NA"
## [373] "NA" "NA"
## [375] "NA" "NA"
## [377] "NA" "NA"
## [379] "NA" "NA"
## [381] "NA" "NA"
## [383] "NA" "NA"
## [385] "NA" "NA"
## [387] "NA" "NA"
## [389] "Diplodus sargus" "Diplodus sargus"
## [391] "Octopus vulgaris" "NA"
## [393] "NA" "NA"
## [395] "NA" "NA"
## [397] "NA" "NA"
## [399] "NA" "NA"
## [401] "NA" "NA"
## [403] "NA" "NA"
## [405] "NA" "NA"
## [407] "NA" "NA"
## [409] "NA" "NA"
## [411] "NA" "NA"
## [413] "NA" "NA"
## [415] "NA" "NA"
## [417] "NA" "NA"
## [419] "NA" "NA"
## [421] "NA" "NA"
## [423] "NA" "NA"
## [425] "NA" "NA"
## [427] "NA" "NA"
## [429] "NA" "NA"
## [431] "NA" "NA"
## [433] "NA" "NA"
## [435] "NA" "NA"
## [437] "NA" "NA"
## [439] "NA" "NA"
## [441] "NA" "NA"
## [443] "NA" "NA"
## [445] "NA" "NA"
## [447] "NA" "NA"
## [449] "NA" "NA"
## [451] "NA" "NA"
## [453] "NA" "NA"
## [455] "NA" "NA"
## [457] "NA" "NA"
## [459] "NA" "NA"
## [461] "NA" "NA"
## [463] "NA" "NA"
## [465] "NA" "NA"
## [467] "NA" "NA"
## [469] "NA" "NA"
## [471] "NA" "NA"
## [473] "NA" "NA"
## [475] "NA" "NA"
## [477] "NA" "NA"
## [479] "NA" "NA"
## [481] "NA" "NA"
## [483] "NA" "NA"
## [485] "NA" "NA"
## [487] "NA" "NA"
## [489] "NA" "NA"
## [491] "NA" "NA"
## [493] "NA" "NA"
## [495] "NA" "NA"
## [497] "NA" "NA"
## [499] "NA" "NA"
## [501] "NA" "NA"
## [503] "NA" "NA"
## [505] "Na" "NA"
## [507] "NA" "NA"
## [509] "NA" "NA"
## [511] "NA" "NA"
## [513] "NA" "NA"
## [515] "NA" "NA"
## [517] "NA" "NA"
## [519] "NA" NA
## [521] NA NA
## [523] NA NA
## [525] NA NA
## [527] NA NA
## [529] NA NA
## [531] NA NA
## [533] NA NA
## [535] NA NA
## [537] NA NA
## [539] NA NA
## [541] NA NA
## [543] NA NA
## [545] NA NA
## [547] NA NA
## [549] NA NA
## [551] NA NA
## [553] NA NA
## [555] NA NA
## [557] NA NA
## [559] NA NA
## [561] NA NA
## [563] NA NA
## [565] NA NA
## [567] NA NA
## [569] NA NA
## [571] NA NA
## [573] NA NA
## [575] NA NA
## [577] NA NA
## [579] NA NA
## [581] NA NA
## [583] NA NA
## [585] NA NA
## [587] NA NA
## [589] NA NA
## [591] NA NA
## [593] NA NA
## [595] NA NA
## [597] NA NA
## [599] NA NA
## [601] NA NA
## [603] NA NA
## [605] NA NA
## [607] NA NA
## [609] NA NA
## [611] NA NA
## [613] NA NA
## [615] NA NA
## [617] NA NA
## [619] NA NA
## [621] NA NA
## [623] NA NA
## [625] NA NA
## [627] NA NA
## [629] NA NA
## [631] NA NA
## [633] NA NA
## [635] NA NA
## [637] NA NA
## [639] NA NA
## [641] NA NA
## [643] NA NA
## [645] NA NA
## [647] NA NA
## [649] NA NA
## [651] NA NA
## [653] NA NA
## [655] NA NA
## [657] NA NA
## [659] NA NA
## [661] NA NA
## [663] NA NA
## [665] NA NA
## [667] NA NA
## [669] NA NA
## [671] NA NA
## [673] NA NA
## [675] NA NA
## [677] NA NA
## [679] NA NA
## [681] NA NA
## [683] NA NA
## [685] NA NA
## [687] NA NA
## [689] NA NA
## [691] NA NA
## [693] NA NA
## [695] NA NA
## [697] NA NA
## [699] "Pagellus erythrinus" "Epinephelus aeneus"
## [701] "Pagrus pagrus" "Seriola dumerilli"
## [703] "NA" "Pagrus pagrus"
## [705] "soupe" "Pagrus pagrus"
## [707] "Dentex dentex" "Diplodus sargus"
## [709] "Pagellus erythrinus" "NA"
## [711] "Seriola dumerilli" "Dentex dentex"
## [713] "Diplodus sargus" "Seriola dumerilli"
## [715] "Coryphaena hippurus" "Dicentrarchus labrax"
## [717] "NA" "Serranus cabrilla"
## [719] "Pagellus erythrinus" "Pagellus erythrinus"
## [721] "Sparus aurata" "NA"
## [723] "NA" "Seriola dumerilli"
## [725] "Pagellus erythrinus" "Pagellus erythrinus"
## [727] "Loligo vulgaris" "Pagellus erythrinus"
## [729] "Pagrus pagrus" "Pagellus erythrinus"
## [731] "NA" "Serranus cabrilla"
## [733] "Seriola dumerilli" "NA"
## [735] "Pagellus erythrinus" "Pagrus pagrus"
## [737] "NA" "Serranus cabrilla"
## [739] "Pagellus erythrinus" "Oblada melanura"
## [741] "Paracentrotus lividuss" "Belone belone"
## [743] "Mullus ssp" "Dicentrarchus labrax"
## [745] "Diplodus sargus" "Sparus aurata"
## [747] "NA" "Mugil cephalus"
## [749] "Pseudocheilinus hexataenia" "Seriola dumerilli"
## [751] "Sphyraena barracuda" "Coris julis"
## [753] "Dentex dentex" "Dicentrarchus labrax"
## [755] "Seriola dumerilli" "racaou"
## [757] "racaou" "Mullus ssp"
## [759] "NA" "Dentex dentex"
## [761] "Dentex dentex" "Pagrus pagrus"
## [763] "Phycis phycis" "Diplodus sargus"
## [765] "Seriola dumerilli" "Dicentrarchus labrax"
## [767] "Dicentrarchus labrax" "Mullus ssp"
## [769] "Labridae" "Labridae"
table(survey$espcib2)
##
## Belone belone Coris julis
## 1 6
## Coryphaena hippurus Dentex dentex
## 1 14
## Dicentrarchus labrax Diplodus sargus
## 11 9
## Diplodus vulgaris Epinephelus aeneus
## 3 1
## Labridae Lichia amia
## 2 2
## Loligo vulgaris Mugil cephalus
## 2 1
## Mullus ssp Na
## 3 1
## NA Oblada melanura
## 453 2
## Octopus vulgaris Pagellus erythrinus
## 1 15
## Pagrus pagrus Paracentrotus lividuss
## 11 1
## Phycis phycis Pseudocheilinus hexataenia
## 1 1
## racaou Richolu
## 2 1
## Sarda sarda Sarpa salpa
## 1 2
## Scorpaena scrofa Seriola dumerilli
## 2 15
## Serranus cabrilla Serranus scriba
## 8 3
## soupe Sparidae
## 2 1
## Sparus aurata Sphyraena barracuda
## 7 1
## Spondyliosoma cantharus toutes
## 1 1
## Trachinotus ovatus Vive
## 1 1
survey$espcib3
## [1] "NA" "NA"
## [3] "NA" "NA"
## [5] "NA" "NA"
## [7] "NA" "NA"
## [9] "NA" "NA"
## [11] "NA" "NA"
## [13] "NA" "NA"
## [15] "NA" "NA"
## [17] "NA" "NA"
## [19] "NA" "NA"
## [21] "NA" "NA"
## [23] "NA" "NA"
## [25] "NA" "NA"
## [27] "NA" "NA"
## [29] "NA" "NA"
## [31] "NA" "NA"
## [33] "NA" "NA"
## [35] "NA" "NA"
## [37] "NA" "NA"
## [39] "NA" "NA"
## [41] "NA" "NA"
## [43] "NA" "NA"
## [45] "NA" "NA"
## [47] "NA" "NA"
## [49] "NA" "NA"
## [51] "NA" "NA"
## [53] "NA" "NA"
## [55] "NA" "NA"
## [57] "NA" "NA"
## [59] "NA" "NA"
## [61] "NA" "NA"
## [63] "NA" "NA"
## [65] "NA" "NA"
## [67] "NA" "NA"
## [69] "NA" "NA"
## [71] "NA" "NA"
## [73] "NA" "NA"
## [75] "NA" "NA"
## [77] "NA" "NA"
## [79] "NA" "NA"
## [81] "NA" "NA"
## [83] "NA" "NA"
## [85] "NA" "NA"
## [87] "NA" "NA"
## [89] "NA" "NA"
## [91] "NA" "NA"
## [93] "NA" "NA"
## [95] "NA" "NA"
## [97] "NA" "NA"
## [99] "NA" "NA"
## [101] "NA" "NA"
## [103] "NA" "NA"
## [105] "NA" "NA"
## [107] "NA" "NA"
## [109] "NA" "NA"
## [111] "NA" "NA"
## [113] "NA" "NA"
## [115] "NA" "NA"
## [117] "NA" "NA"
## [119] "NA" "NA"
## [121] "NA" "NA"
## [123] "NA" "NA"
## [125] "NA" "NA"
## [127] "NA" "NA"
## [129] "NA" "NA"
## [131] "NA" "NA"
## [133] "NA" "NA"
## [135] "NA" "NA"
## [137] "NA" "NA"
## [139] "NA" "NA"
## [141] "NA" "NA"
## [143] "NA" "NA"
## [145] "NA" "NA"
## [147] "NA" "NA"
## [149] "NA" "NA"
## [151] "NA" "NA"
## [153] "NA" "NA"
## [155] "NA" "NA"
## [157] "NA" "NA"
## [159] "NA" "NA"
## [161] "NA" "NA"
## [163] "NA" "NA"
## [165] "NA" "NA"
## [167] "NA" "Dicentrarchus labrax"
## [169] "NA" "NA"
## [171] "Diplodus vulgaris" "Lichia amia"
## [173] "NA" "Seriola dumerilli"
## [175] "Dentex dentex" "NA"
## [177] "NA" "NA"
## [179] "soupe" "Coris julis"
## [181] "toutes" "NA"
## [183] "soupe" "NA"
## [185] "NA" "NA"
## [187] "NA" "NA"
## [189] "Seriola dumerilli" "Dentex dentex"
## [191] "Lichia amia" "toutes"
## [193] "Sparus aurata" "NA"
## [195] "NA" "NA"
## [197] "Sparus aurata" "Sparus aurata"
## [199] "Serranus cabrilla" "Dicentrarchus labrax"
## [201] "Zeus faber" "Sparidae"
## [203] "NA" "NA"
## [205] "Labridae" "NA"
## [207] "NA" "NA"
## [209] "NA" "Dentex dentex"
## [211] "Pagellus erythrinus" "NA"
## [213] "NA" "NA"
## [215] "NA" "NA"
## [217] "NA" "NA"
## [219] "NA" "NA"
## [221] "NA" "NA"
## [223] "Pagrus pagrus" "Diplodus vulgaris"
## [225] "Diplodus vulgaris" "NA"
## [227] "Dicentrarchus labrax" "NA"
## [229] "Diplodus sargus" "Serranus cabrilla"
## [231] "Sphyraena barracuda" "NA"
## [233] "Dicentrarchus labrax" "Serranus scriba"
## [235] "Serranu scriba" "NA"
## [237] "NA" "Diplodus sargus"
## [239] "Pagellus erythrinus" "Serranus scriba"
## [241] "Thunnus thynnus" "Sparus aurata"
## [243] "NA" "Pagellus erythrinus"
## [245] "Maquereau" "Serranus scriba"
## [247] "Sparus aurata" "Paracentrotus lividus"
## [249] "NA" "NA"
## [251] "NA" "NA"
## [253] "Coris julis" "Coris julis"
## [255] "Sphyraena barracuda" "Sparus aurata"
## [257] "NA" "NA"
## [259] "Diplodus sargus" "Pagrus pagrus"
## [261] "NA" "NA"
## [263] "NA" "NA"
## [265] "NA" "NA"
## [267] "NA" "NA"
## [269] "NA" "NA"
## [271] "NA" "NA"
## [273] "NA" "NA"
## [275] "NA" "NA"
## [277] "NA" "NA"
## [279] "NA" "NA"
## [281] "NA" "NA"
## [283] "NA" "NA"
## [285] "NA" "NA"
## [287] "NA" "NA"
## [289] "NA" "NA"
## [291] "NA" "NA"
## [293] "NA" "NA"
## [295] "NA" "NA"
## [297] "NA" "NA"
## [299] "NA" "NA"
## [301] "NA" "NA"
## [303] "NA" "NA"
## [305] "NA" "NA"
## [307] "NA" "NA"
## [309] "NA" "NA"
## [311] "NA" "NA"
## [313] "NA" "NA"
## [315] "NA" "NA"
## [317] "NA" "NA"
## [319] "NA" "NA"
## [321] "NA" "NA"
## [323] "NA" "NA"
## [325] "NA" "NA"
## [327] "NA" "NA"
## [329] "NA" "NA"
## [331] "NA" "NA"
## [333] "NA" "NA"
## [335] "NA" "NA"
## [337] "NA" "NA"
## [339] "NA" "NA"
## [341] "NA" "NA"
## [343] "NA" "NA"
## [345] "NA" "NA"
## [347] "NA" "NA"
## [349] "NA" "NA"
## [351] "NA" "NA"
## [353] "NA" "NA"
## [355] "NA" "NA"
## [357] "NA" "NA"
## [359] "NA" "NA"
## [361] "NA" "NA"
## [363] "NA" "NA"
## [365] "NA" "NA"
## [367] "NA" "NA"
## [369] "NA" "NA"
## [371] "NA" "NA"
## [373] "NA" "NA"
## [375] "NA" "NA"
## [377] "NA" "NA"
## [379] "NA" "NA"
## [381] "NA" "NA"
## [383] "NA" "NA"
## [385] "NA" "NA"
## [387] "NA" "NA"
## [389] "NA" "NA"
## [391] "NA" "NA"
## [393] "NA" "NA"
## [395] "NA" "NA"
## [397] "NA" "NA"
## [399] "NA" "NA"
## [401] "NA" "NA"
## [403] "NA" "NA"
## [405] "NA" "NA"
## [407] "NA" "NA"
## [409] "NA" "NA"
## [411] "NA" "NA"
## [413] "NA" "NA"
## [415] "NA" "NA"
## [417] "NA" "NA"
## [419] "NA" "NA"
## [421] "NA" "NA"
## [423] "NA" "NA"
## [425] "NA" "NA"
## [427] "NA" "NA"
## [429] "NA" "NA"
## [431] "NA" "NA"
## [433] "NA" "NA"
## [435] "NA" "NA"
## [437] "NA" "NA"
## [439] "NA" "NA"
## [441] "NA" "NA"
## [443] "NA" "NA"
## [445] "NA" "NA"
## [447] "NA" "NA"
## [449] "NA" "NA"
## [451] "NA" "NA"
## [453] "NA" "NA"
## [455] "NA" "NA"
## [457] "NA" "NA"
## [459] "NA" "NA"
## [461] "NA" "NA"
## [463] "NA" "NA"
## [465] "NA" "NA"
## [467] "NA" "NA"
## [469] "NA" "NA"
## [471] "NA" "NA"
## [473] "NA" "NA"
## [475] "NA" "NA"
## [477] "NA" "NA"
## [479] "NA" "NA"
## [481] "NA" "NA"
## [483] "NA" "NA"
## [485] "NA" "NA"
## [487] "NA" "NA"
## [489] "NA" "NA"
## [491] "NA" "NA"
## [493] "NA" "NA"
## [495] "NA" "NA"
## [497] "NA" "NA"
## [499] "NA" "NA"
## [501] "NA" "NA"
## [503] "NA" "NA"
## [505] "NA" "NA"
## [507] "NA" "NA"
## [509] "NA" "NA"
## [511] "NA" "NA"
## [513] "NA" "NA"
## [515] "NA" "NA"
## [517] "NA" "NA"
## [519] "NA" NA
## [521] NA NA
## [523] NA NA
## [525] NA NA
## [527] NA NA
## [529] NA NA
## [531] NA NA
## [533] NA NA
## [535] NA NA
## [537] NA NA
## [539] NA NA
## [541] NA NA
## [543] NA NA
## [545] NA NA
## [547] NA NA
## [549] NA NA
## [551] NA NA
## [553] NA NA
## [555] NA NA
## [557] NA NA
## [559] NA NA
## [561] NA NA
## [563] NA NA
## [565] NA NA
## [567] NA NA
## [569] NA NA
## [571] NA NA
## [573] NA NA
## [575] NA NA
## [577] NA NA
## [579] NA NA
## [581] NA NA
## [583] NA NA
## [585] NA NA
## [587] NA NA
## [589] NA NA
## [591] NA NA
## [593] NA NA
## [595] NA NA
## [597] NA NA
## [599] NA NA
## [601] NA NA
## [603] NA NA
## [605] NA NA
## [607] NA NA
## [609] NA NA
## [611] NA NA
## [613] NA NA
## [615] NA NA
## [617] NA NA
## [619] NA NA
## [621] NA NA
## [623] NA NA
## [625] NA NA
## [627] NA NA
## [629] NA NA
## [631] NA NA
## [633] NA NA
## [635] NA NA
## [637] NA NA
## [639] NA NA
## [641] NA NA
## [643] NA NA
## [645] NA NA
## [647] NA NA
## [649] NA NA
## [651] NA NA
## [653] NA NA
## [655] NA NA
## [657] NA NA
## [659] NA NA
## [661] NA NA
## [663] NA NA
## [665] NA NA
## [667] NA NA
## [669] NA NA
## [671] NA NA
## [673] NA NA
## [675] NA NA
## [677] NA NA
## [679] NA NA
## [681] NA NA
## [683] NA NA
## [685] NA NA
## [687] NA NA
## [689] NA NA
## [691] NA NA
## [693] NA NA
## [695] NA NA
## [697] NA NA
## [699] "soupe" "Dicentrarchus labrax"
## [701] "Dentex dentex" "Sparus aurata"
## [703] "NA" "Scorpaena scrofa"
## [705] "NA" "Seriola dumerilli"
## [707] "Seriola dumerilli" "NA"
## [709] "Sparus aurata" "NA"
## [711] "Diplodus sargus" "Sphyraena barracuda"
## [713] "Dicentrarchus labrax" "Luligo vulgaris"
## [715] "Euthynnus alletteratus" "Dentex dentex"
## [717] "NA" "Diplodus sargus"
## [719] "Serranus cabrilla" "Dentex dentex"
## [721] "soupe" "NA"
## [723] "NA" "Sarda sarda"
## [725] "NA" "NA"
## [727] "Pagellus erythrinus" "NA"
## [729] "Pagellus bogaraveo" "Scorpaena scrofa"
## [731] "NA" "Coris julis"
## [733] "Pagrus pagrus" "NA"
## [735] "NA" "Pagellus bogaraveo"
## [737] "NA" "NA"
## [739] "soupe" "Dentex dentex"
## [741] "NA" "Sparus aurata"
## [743] "Sparus aurata" "Sparus aurata"
## [745] "Scorpaena scrofa" "Seriola dumerilli"
## [747] "NA" "Dicentrarchus labrax"
## [749] "Mugil cephalus" "Sphyraena barracuda"
## [751] "Pseudocheilinus hexataenia" "Diplodus sargus"
## [753] "Trachurus trachurus" "Sparus aurata"
## [755] "Scorpaena scrofa" "Dicentrarchus labrax"
## [757] "Dicentrarchus labrax" "Diplodus sargus"
## [759] "NA" "Seriola dumerilli"
## [761] "Seriola dumerilli" "Dentex dentex"
## [763] "Sphyraena barracuda" "Phycis phycis"
## [765] "Lichia amia" "Mugil cephalus"
## [767] "Mullus ssp" "Labridae"
## [769] "Sparus aurata" "Oblada melanura"
table(survey$espcib3)
##
## Coris julis Dentex dentex
## 4 8
## Dicentrarchus labrax Diplodus sargus
## 9 7
## Diplodus vulgaris Euthynnus alletteratus
## 3 1
## Labridae Lichia amia
## 2 3
## Luligo vulgaris Maquereau
## 1 1
## Mugil cephalus Mullus ssp
## 2 1
## NA Oblada melanura
## 488 1
## Pagellus bogaraveo Pagellus erythrinus
## 2 4
## Pagrus pagrus Paracentrotus lividus
## 3 1
## Phycis phycis Pseudocheilinus hexataenia
## 1 1
## Sarda sarda Scorpaena scrofa
## 1 4
## Seriola dumerilli Serranu scriba
## 7 1
## Serranus cabrilla Serranus scriba
## 3 3
## soupe Sparidae
## 5 1
## Sparus aurata Sphyraena barracuda
## 13 5
## Thunnus thynnus toutes
## 1 2
## Trachurus trachurus Zeus faber
## 1 1
df. <- survey[, c("a", "espcib1", "espcib2", "espcib3")]
#saveRDS(df., "df.rds") # for ChatGPT
plot.bar.sp <- function(var., title.) {
df_clean <- df.sp[,var.] %>%
filter(df.sp[,var.] != "NA") %>%
na.omit() %>%
pivot_longer(everything(), names_to = "variable", values_to = "value") %>%
group_by(variable, value) %>%
summarise(count = n(), .groups = 'drop') %>%
mutate(total = sum(count), percentage = (count / total) * 100) %>%
arrange(desc(count))
ggplot(df_clean, aes(x = reorder(value, percentage), y = percentage)) +
geom_bar(stat = "identity", colour = 'mediumblue', fill = "mediumblue", width = 0.5) +
scale_y_continuous(expand = c(0, 0)) +
geom_text(aes(label = count, y = percentage + 1), hjust = 1.1, color = "black", size = 3.5) +
#facet_wrap(~variable, scales = "free_y") +
labs(x = "Species", y = "Percentage of fishers") +
ggtitle(paste0(title., " (N=", sum(df_clean$count),")")) +
#theme_minimal() +
#theme(axis.text.x = element_text(angle = 0, hjust = 1)) +
coord_flip() +
theme(panel.background=element_blank(), axis.line = element_line(), axis.ticks.y =element_blank())
}
df. %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> df.sp
plot.bar.sp(var. = "espcib1", title. = "Espèce cible 1 2020-2023")
## Warning: Using one column matrices in `filter()` was deprecated in dplyr 1.1.0.
## ℹ Please use one dimensional logical vectors instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
ggsave("Figs/Espece/espece.cible.1_2020-2023.png", width = 7, height = 7)
df. %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> df.sp
plot.bar.sp(var. = "espcib2", title. = "Espèce cible 2 2020-2023")
ggsave("Figs/Espece/espece.cible.2_2020-2023.png", width = 7, height = 7)
df. %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> df.sp
plot.bar.sp(var. = "espcib3", title. = "Espèce cible 3 2020-2023")
ggsave("Figs/Espece/espece.cible.3_2020-2023.png", width = 7, height = 7)
df. %>% filter(a %in% c("2020", "2021", "2022")) -> df.sp
plot.bar.sp(var. = "espcib1", title. = "Espèce cible 1 2020-2022")
ggsave("Figs/Espece/espece.cible.1_2020-2022.png", width = 7, height = 7)
df. %>% filter(a %in% c("2020", "2021", "2022")) -> df.sp
plot.bar.sp(var. = "espcib2", title. = "Espèce cible 2 2020-2022")
ggsave("Figs/Espece/espece.cible.2_2020-2022.png", width = 7, height = 7)
df. %>% filter(a %in% c("2020", "2021", "2022")) -> df.sp
plot.bar.sp(var. = "espcib3", title. = "Espèce cible 3 2020-2022")
ggsave("Figs/Espece/espece.cible.3_2020-2022.png", width = 7, height = 7)
df. %>% filter(a %in% c("2023")) -> df.sp
plot.bar.sp(var. = "espcib1", title. = "Espèce cible 1 2023")
ggsave("Figs/Espece/espece.cible.1_2023.png", width = 7, height = 7)
df. %>% filter(a %in% c("2023")) -> df.sp
plot.bar.sp(var. = "espcib2", title. = "Espèce cible 2 2023")
ggsave("Figs/Espece/espece.cible.2_2023.png", width = 7, height = 7)
df. %>% filter(a %in% c("2023")) -> df.sp
plot.bar.sp(var. = "espcib3", title. = "Espèce cible 3 2023")
ggsave("Figs/Espece/espece.cible.3_2023.png", width = 7, height = 7)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red", "results_df", "results_df.1", "results_df.2")))
# plot species and biomass fished ####
df.fsh <- fishing[, c("a", "nom_scien", "nb_ind", "tail_cm", "poids_g")]
#saveRDS(df.fsh, "df.fsh.rds") # for ChatGPT
unique(df.fsh$nom_scien)
## [1] "Dicentrarchus labrax" "Diplodus sargus"
## [3] "Mullus surmuletus" "Pagellus erythrinus"
## [5] "Serranus cabrilla" "Trachinus draco"
## [7] "Euthynnus alletteratus" "Spondyliosoma cantharus"
## [9] "Labrus merula" "Mugil sp"
## [11] "Coris julis" "Serranus scriba"
## [13] "Scomber scombrus" "Boops boops"
## [15] "Trachurus trachurus" "Loligo sp"
## [17] "Dentex dentex" "Pagrus pagrus"
## [19] "Helicolenus dactylopterus" "Seriola dumerili"
## [21] "Octopus vulgaris" "Sphyraena viridensis"
## [23] "Synodus saurus" "Spondiliosomas cantharus"
## [25] "Polyprion americanus" "Labrus mixtus"
## [27] "Muraena helena" "Loligo spp"
## [29] "Oblada melanura" "Diplodus vulgaris"
## [31] "Diplodus annularis" "Sparus aurata"
## [33] "Sarpa salpa" "Trachinus radiatus"
## [35] "Pagellus bogaraveo" "Labrus bergylta"
## [37] "Conger conger" "Loligo ssp"
## [39] "Echiichthys vipera" "Scorpaena porcus"
## [41] "Spondyliosoma cantharus " "Trachinus sp."
## [43] "Scorpaena scrofa" "Chelon labrosus"
## [45] "Lithognathus mormyrus" "Mullus spp"
## [47] "Labrus viridis" "Thalassoma pavo"
## [49] "Coryphaena hippurus" "Chromis chromis"
## [51] "Symphodus roissali" "Epinephelus marginatus"
## [53] "Diplodus puntazzo" "Sphyraena barracuda"
## [55] "Seriola dumerilii" "Loligo vulgaris"
## [57] "Raja sp." "Diplodus Sargus"
## [59] "Xyrichthys novacula" "Umbrina cirrosa"
## [61] "Symphodus tinca" "0"
## [63] "Scorpaena scofa" "NA"
## [65] "serranus sp." "Mugil sp."
## [67] "Spicara maena" "Dasyatis pastinaca"
## [69] "crabes" "gobie"
## [71] "Sphyraena sp." "Sepia officinalis"
## [73] "Diplodus sp." "calamar rouge"
## [75] "Liligo sp." "Serranus sp."
df.fsh %>% filter(nom_scien %notin% c("0", "NA")) -> df.fsh
sum(df.fsh$poids_g, na.rm = TRUE)
## [1] 228499.6
sum(df.fsh$nb_ind, na.rm = TRUE)
## [1] 2335
#NB: I think there are some species fished but not weighed!
plot.bar.fsh <- function(title.) {
df_sum <- df.fsh.red %>%
group_by(nom_scien) %>%
summarise(total_poids_g = round(sum(poids_g, na.rm = TRUE), digits = 0),
perc_poids_g = round((sum(poids_g, na.rm = TRUE)/(sum(df.fsh$poids_g, na.rm = TRUE)))*100, digits = 2),
.groups = 'drop')
ggplot(df_sum, aes(x = reorder(nom_scien, perc_poids_g), y = log10(perc_poids_g+1), group = 1)) +
geom_point(colour = 'mediumblue') +
geom_segment(aes(xend=nom_scien), yend=0, colour = 'mediumblue') +
scale_y_continuous(expand = c(0, 0)) +
geom_text(aes(label = total_poids_g, y = log10(perc_poids_g+1)+0.05), hjust = 1.1, color = "black", size = 2.5) +
#facet_wrap(~variable, scales = "free_y") +
labs(x = "Species", y = expression(Log[10](biomasse~pêchée~+~1))) +
ggtitle(paste0(title., " (somme = ", sum(df_sum$total_poids_g)," g)")) +
#theme_minimal() +
#theme(axis.text.x = element_text(angle = 0, hjust = 1)) +
coord_flip() +
theme(panel.background=element_blank(), axis.line = element_line(), axis.ticks.y =element_blank())
}
df.fsh %>% filter(a %in% c("2020", "2021", "2022", "2023") & poids_g != 0) -> df.fsh.red
plot.bar.fsh(title. = "Biomasse pêchée en 2020-2023")
ggsave("Figs/Biomasse/biomasse_2020-2023.png", width = 7, height = 7)
df.fsh %>% filter(a %in% c("2020", "2021", "2022") & poids_g != 0) -> df.fsh.red
plot.bar.fsh(title. = "Biomasse pêchée en 2020-2022")
ggsave("Figs/Biomasse/biomasse_2020-2022.png", width = 7, height = 7)
df.fsh %>% filter(a %in% c("2023") & poids_g != 0) -> df.fsh.red
plot.bar.fsh(title. = "Biomasse pêchée en 2023")
ggsave("Figs/Biomasse/biomasse_2023.png", width = 7, height = 7)
plot.bar.fsh <- function(title.) {
df_sum <- df.fsh.red %>%
group_by(nom_scien) %>%
summarise(total_nb_ind = sum(nb_ind, na.rm = TRUE),
perc_nb_ind = (sum(nb_ind, na.rm = TRUE)/(sum(df.fsh$nb_ind, na.rm = TRUE)))*100,
.groups = 'drop')
ggplot(df_sum, aes(x = reorder(nom_scien, perc_nb_ind), y = log10(perc_nb_ind+1), group = 1)) +
geom_point(colour = 'mediumblue') +
geom_segment(aes(xend=nom_scien), yend=0, colour = 'mediumblue') +
scale_y_continuous(expand = c(0, 0)) +
geom_text(aes(label = total_nb_ind, y = log10(perc_nb_ind+1)+0.05), hjust = 1.1, color = "black", size = 2.5) +
#facet_wrap(~variable, scales = "free_y") +
labs(x = "Species", y = expression(Log[10](percentage~of~individuals~+~1))) +
ggtitle(paste0(title., " (N=", sum(df_sum$total_nb_ind),")")) +
#theme_minimal() +
#theme(axis.text.x = element_text(angle = 0, hjust = 1)) +
coord_flip() +
theme(panel.background=element_blank(), axis.line = element_line(), axis.ticks.y =element_blank())
}
df.fsh %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> df.fsh.red
plot.bar.fsh(title. = "Individus pêchés en 2020-2023")
ggsave("Figs/Individu/individu_2020-2023.png", width = 7, height = 7)
df.fsh %>% filter(a %in% c("2020", "2021", "2022")) -> df.fsh.red
plot.bar.fsh(title. = "Individus pêchés en 2020-2022")
ggsave("Figs/Individu/individu_2020-2022.png", width = 7, height = 7)
df.fsh %>% filter(a %in% c("2023")) -> df.fsh.red
plot.bar.fsh(title. = "Individus pêchés en 2023")
ggsave("Figs/Individu/individu_2023.png", width = 7, height = 7)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red", "results_df", "results_df.1", "results_df.2")))
# plot main fish species caught by size class ####
df.fsh <- fishing[, c("a", "nom_scien", "nb_ind", "tail_cm", "poids_g")]
#saveRDS(df.fsh, "df.fsh.rds") # for ChatGPT
unique(df.fsh$nom_scien)
## [1] "Dicentrarchus labrax" "Diplodus sargus"
## [3] "Mullus surmuletus" "Pagellus erythrinus"
## [5] "Serranus cabrilla" "Trachinus draco"
## [7] "Euthynnus alletteratus" "Spondyliosoma cantharus"
## [9] "Labrus merula" "Mugil sp"
## [11] "Coris julis" "Serranus scriba"
## [13] "Scomber scombrus" "Boops boops"
## [15] "Trachurus trachurus" "Loligo sp"
## [17] "Dentex dentex" "Pagrus pagrus"
## [19] "Helicolenus dactylopterus" "Seriola dumerili"
## [21] "Octopus vulgaris" "Sphyraena viridensis"
## [23] "Synodus saurus" "Spondiliosomas cantharus"
## [25] "Polyprion americanus" "Labrus mixtus"
## [27] "Muraena helena" "Loligo spp"
## [29] "Oblada melanura" "Diplodus vulgaris"
## [31] "Diplodus annularis" "Sparus aurata"
## [33] "Sarpa salpa" "Trachinus radiatus"
## [35] "Pagellus bogaraveo" "Labrus bergylta"
## [37] "Conger conger" "Loligo ssp"
## [39] "Echiichthys vipera" "Scorpaena porcus"
## [41] "Spondyliosoma cantharus " "Trachinus sp."
## [43] "Scorpaena scrofa" "Chelon labrosus"
## [45] "Lithognathus mormyrus" "Mullus spp"
## [47] "Labrus viridis" "Thalassoma pavo"
## [49] "Coryphaena hippurus" "Chromis chromis"
## [51] "Symphodus roissali" "Epinephelus marginatus"
## [53] "Diplodus puntazzo" "Sphyraena barracuda"
## [55] "Seriola dumerilii" "Loligo vulgaris"
## [57] "Raja sp." "Diplodus Sargus"
## [59] "Xyrichthys novacula" "Umbrina cirrosa"
## [61] "Symphodus tinca" "0"
## [63] "Scorpaena scofa" "NA"
## [65] "serranus sp." "Mugil sp."
## [67] "Spicara maena" "Dasyatis pastinaca"
## [69] "crabes" "gobie"
## [71] "Sphyraena sp." "Sepia officinalis"
## [73] "Diplodus sp." "calamar rouge"
## [75] "Liligo sp." "Serranus sp."
df.fsh %>% filter(nom_scien %notin% c("0", "NA")) -> df.fsh
unique(df.fsh$nom_scien)
## [1] "Dicentrarchus labrax" "Diplodus sargus"
## [3] "Mullus surmuletus" "Pagellus erythrinus"
## [5] "Serranus cabrilla" "Trachinus draco"
## [7] "Euthynnus alletteratus" "Spondyliosoma cantharus"
## [9] "Labrus merula" "Mugil sp"
## [11] "Coris julis" "Serranus scriba"
## [13] "Scomber scombrus" "Boops boops"
## [15] "Trachurus trachurus" "Loligo sp"
## [17] "Dentex dentex" "Pagrus pagrus"
## [19] "Helicolenus dactylopterus" "Seriola dumerili"
## [21] "Octopus vulgaris" "Sphyraena viridensis"
## [23] "Synodus saurus" "Spondiliosomas cantharus"
## [25] "Polyprion americanus" "Labrus mixtus"
## [27] "Muraena helena" "Loligo spp"
## [29] "Oblada melanura" "Diplodus vulgaris"
## [31] "Diplodus annularis" "Sparus aurata"
## [33] "Sarpa salpa" "Trachinus radiatus"
## [35] "Pagellus bogaraveo" "Labrus bergylta"
## [37] "Conger conger" "Loligo ssp"
## [39] "Echiichthys vipera" "Scorpaena porcus"
## [41] "Spondyliosoma cantharus " "Trachinus sp."
## [43] "Scorpaena scrofa" "Chelon labrosus"
## [45] "Lithognathus mormyrus" "Mullus spp"
## [47] "Labrus viridis" "Thalassoma pavo"
## [49] "Coryphaena hippurus" "Chromis chromis"
## [51] "Symphodus roissali" "Epinephelus marginatus"
## [53] "Diplodus puntazzo" "Sphyraena barracuda"
## [55] "Seriola dumerilii" "Loligo vulgaris"
## [57] "Raja sp." "Diplodus Sargus"
## [59] "Xyrichthys novacula" "Umbrina cirrosa"
## [61] "Symphodus tinca" "Scorpaena scofa"
## [63] "serranus sp." "Mugil sp."
## [65] "Spicara maena" "Dasyatis pastinaca"
## [67] "crabes" "gobie"
## [69] "Sphyraena sp." "Sepia officinalis"
## [71] "Diplodus sp." "calamar rouge"
## [73] "Liligo sp." "Serranus sp."
df.fsh %>% filter(a %in% c("2020", "2021", "2022", "2023")) -> df.fsh.red
df_sum <- df.fsh.red %>%
group_by(nom_scien) %>%
summarise(total_nb_ind = sum(nb_ind, na.rm = TRUE),
perc_nb_ind = (sum(nb_ind, na.rm = TRUE)/(sum(df.fsh.red$nb_ind, na.rm = TRUE)))*100,
.groups = 'drop')
df_sum <-df_sum[order(df_sum$total_nb_ind, decreasing = T),]
df.fsh %>% filter(a %in% c("2020", "2021", "2022")) -> df.fsh.red.1
df_sum.1 <- df.fsh.red.1 %>%
group_by(nom_scien) %>%
summarise(total_nb_ind = sum(nb_ind, na.rm = TRUE),
perc_nb_ind = (sum(nb_ind, na.rm = TRUE)/(sum(df.fsh.red.1$nb_ind, na.rm = TRUE)))*100,
.groups = 'drop')
df_sum.1 <-df_sum.1[order(df_sum.1$total_nb_ind, decreasing = T),]
df.fsh %>% filter(a %in% c("2023")) -> df.fsh.red.2
df_sum.2 <- df.fsh.red.2 %>%
group_by(nom_scien) %>%
summarise(total_nb_ind = sum(nb_ind, na.rm = TRUE),
perc_nb_ind = (sum(nb_ind, na.rm = TRUE)/(sum(df.fsh.red.2$nb_ind, na.rm = TRUE)))*100,
.groups = 'drop')
df_sum.2 <-df_sum.2[order(df_sum.2$total_nb_ind, decreasing = T),]
sort(df_sum$nom_scien[1:6])
## [1] "Coris julis" "Diplodus annularis"
## [3] "Pagellus erythrinus" "Serranus cabrilla"
## [5] "Serranus scriba" "Spondyliosoma cantharus"
sort(df_sum.1$nom_scien[1:6])
## [1] "Coris julis" "Diplodus annularis" "Loligo sp"
## [4] "Pagellus erythrinus" "Serranus cabrilla" "Serranus scriba"
sort(df_sum.2$nom_scien[1:6])
## [1] "Coris julis" "Diplodus annularis"
## [3] "Diplodus sargus" "Serranus cabrilla"
## [5] "Serranus scriba" "Spondyliosoma cantharus"
sp. <- unique(sort(c(df_sum$nom_scien[1:6], df_sum.1$nom_scien[1:6])))
sp. <- unique(sort(c(sp., df_sum.2$nom_scien[1:6])))
(sort(sp.))
## [1] "Coris julis" "Diplodus annularis"
## [3] "Diplodus sargus" "Loligo sp"
## [5] "Pagellus erythrinus" "Serranus cabrilla"
## [7] "Serranus scriba" "Spondyliosoma cantharus"
size.at.maturity <- data.frame(species = sp.,
size.mat = c(18, #"Coris julis", Michel
12, #"Diplodus annularis", Michel (7, Lovina)
6, #"Diplodus sargus", Lovina "Listing medfish characteristics Dimarchopoulou et al. 2016.xlsx"
round((17.6+15.3)/2,0), #"Loligo sp", "The ML 50% of females was estimated to be 17.6 cm. The ML 50% of males was estimated to be 15.3 cm." Moreno et al., Aquat. Living Resour. 18, 377–384 (2005), Environmental influences on age and size at maturity of Loligo vulgaris
10, #"Pagellus erythrinus", Michel (9, Lovina)
4, #"Serranus cabrilla", Lovina "Listing medfish characteristics Dimarchopoulou et al. 2016.xlsx"
16, #"Serranus scriba", Michel
19 #"Spondyliosoma cantharus", Michel
))
size.sp. <- function(df.fsh., df., years.) {
#df.fsh.=df.fsh.red.1
#df.=df_sum.1
#years.="2020-2022"
for(i in c(1:6)) {
#i=1
df.i <- filter(df.fsh., nom_scien == sort(df.[1:6,"nom_scien"]$nom_scien)[i])
print(sp. <- unclass(unique(filter(df.fsh., nom_scien == sort(df.[1:6,"nom_scien"]$nom_scien)[i])["nom_scien"]))$nom_scien)
(sexsize=(filter(size.at.maturity,species==sp.))["size.mat"]$size.mat)
filter(df.fsh., nom_scien == sp.)
hist(unlist(filter(df.fsh., nom_scien == sp.)[,"tail_cm"]), xlab = "size (cm)", main = sp.)
(data <- df.i$tail_cm)
(border_value <- sexsize)
# Split data into two parts based on the border value
(data_left <- na.omit(data[data < border_value]))
(data_right <- na.omit(data[data >= border_value]))
# Determine the number of groups on each side
total_groups <- 5
(left_proportion <- (sexsize-min(data, na.rm = T))/(max(data, na.rm = T)-min(data, na.rm = T)))
(left_proportion <- ifelse(left_proportion < 0, 0, left_proportion))
(right_proportion <- (max(data, na.rm = T)-sexsize)/(max(data, na.rm = T)-min(data, na.rm = T)))
(right_proportion <- ifelse(right_proportion > 1, 1, right_proportion))
(left_groups <- round(left_proportion * total_groups))
(right_groups <- total_groups - left_groups)
# Define breaks for left side
(if (length(data_left) > 0) {
left_breaks <- seq(min(data_left), sexsize, length.out = left_groups + 1)
} else {
left_breaks <- NULL
})
# Define breaks for right side
(if (length(data_right) > 0) {
right_breaks <- seq(sexsize, max(data_right), length.out = right_groups + 1)
} else {
right_breaks <- NULL
})
# Combine breaks
(breaks <- unique(c(left_breaks, right_breaks)))
(breaks <- round(breaks))
s.cl <- breaks
(s.cl.range <- c(paste0("[",s.cl[1],"-",s.cl[2],"["), paste0("[",s.cl[2],"-",s.cl[3],"["), paste0("[",s.cl[3],"-",s.cl[4],"["),paste0("[",s.cl[4],"-",s.cl[5],"["), paste0("[",s.cl[5],"-",s.cl[6],"]")))
df.i$tail_cm_classe <- NA
df.i$tail_cm_classe <- ifelse(df.i$tail_cm < s.cl[2], paste0("[",s.cl[1],"-",s.cl[2],"["), df.i$tail_cm_classe)
df.i$tail_cm_classe <- ifelse(df.i$tail_cm < s.cl[3] & is.na(df.i$tail_cm_classe), paste0("[",s.cl[2],"-",s.cl[3],"["), df.i$tail_cm_classe)
df.i$tail_cm_classe <- ifelse(df.i$tail_cm < s.cl[4] & is.na(df.i$tail_cm_classe), paste0("[",s.cl[3],"-",s.cl[4],"["), df.i$tail_cm_classe)
df.i$tail_cm_classe <- ifelse(df.i$tail_cm < s.cl[5] & is.na(df.i$tail_cm_classe), paste0("[",s.cl[4],"-",s.cl[5],"["), df.i$tail_cm_classe)
df.i$tail_cm_classe <- ifelse(df.i$tail_cm <= s.cl[6] & is.na(df.i$tail_cm_classe), paste0("[",s.cl[5],"-",s.cl[6],"]"), df.i$tail_cm_classe)
df.i$tail_cm_classe <- as.factor(df.i$tail_cm_classe)
as.character(na.omit(unique(df.i$tail_cm_classe)))
setdiff(s.cl.range, as.character(na.omit(unique(df.i$tail_cm_classe))))
ifelse(length(setdiff(s.cl.range, as.character(na.omit(unique(df.i$tail_cm_classe))))) >=1, df.i <- add_row(df.i, tail_cm_classe = setdiff(s.cl.range, as.character(na.omit(unique(df.i$tail_cm_classe))))), df.i)
df.i$tail_cm_classe <- factor(df.i$tail_cm_classe, levels = c(paste0("[",s.cl[1],"-",s.cl[2],"["), paste0("[",s.cl[2],"-",s.cl[3],"["), paste0("[",s.cl[3],"-",s.cl[4],"["),paste0("[",s.cl[4],"-",s.cl[5],"["), paste0("[",s.cl[5],"-",s.cl[6],"]")))
levels(df.i$tail_cm_classe)
#df.i <- na.omit(df.i[,c("tail_cm", "tail_cm_classe")])
#levels(df.i$tail_cm_classe)
df.i$tail_cm_classe.num <- NA
df.i$tail_cm_classe.num <- ifelse(df.i$tail_cm_classe == paste0("[",s.cl[1],"-",s.cl[2],"["), 1, df.i$tail_cm_classe.num)
df.i$tail_cm_classe.num <- ifelse(df.i$tail_cm_classe == paste0("[",s.cl[2],"-",s.cl[3],"["), 2, df.i$tail_cm_classe.num)
df.i$tail_cm_classe.num <- ifelse(df.i$tail_cm_classe == paste0("[",s.cl[3],"-",s.cl[4],"["), 3, df.i$tail_cm_classe.num)
df.i$tail_cm_classe.num <- ifelse(df.i$tail_cm_classe == paste0("[",s.cl[4],"-",s.cl[5],"["), 4, df.i$tail_cm_classe.num)
df.i$tail_cm_classe.num <- ifelse(df.i$tail_cm_classe == paste0("[",s.cl[5],"-",s.cl[6],"]"), 5, df.i$tail_cm_classe.num)
df.i$tail_cm_classe.num <- as.integer(df.i$tail_cm_classe.num)
(df.i$tail_cm_classe.num)
(txt. <- paste0("[",sexsize,"-"))
(threshold_category <- unlist(unique((df.i[grep(paste0("\\",txt.), df.i$tail_cm_classe), ])$tail_cm_classe.num)))
df.i$mature <- NA
df.i$mature <- ifelse(df.i$tail_cm_classe.num < threshold_category, "non", "oui")
df.i$mature <- as.factor(df.i$mature)
df.i.narm <- na.omit(df.i[, c("tail_cm", "tail_cm_classe", "tail_cm_classe.num", "mature")])
print(table(df.i.narm[, c("tail_cm_classe", "tail_cm_classe.num", "mature")]))
df.i.narm %>% group_by(tail_cm_classe, mature) %>% summarise(n())
barplot.i <- ggplot(df.i.narm, aes(x = tail_cm_classe, fill = mature)) +
geom_bar() +
scale_x_discrete(drop=FALSE) +
scale_fill_manual(values = c("non" = "orange", "oui" = "lightblue")) +
labs(title = paste0(unique(df.i$nom_scien), " (N = ", nrow(df.i.narm), ", ", years., ")"),
x = "Taille (cm)",
y = "Nombre d'individus",
fill = "Mature") +
theme_bw() +
theme(axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank()) +
scale_y_continuous(expand = c(0,0))
barplot.i <- barplot.i + ggtitle(bquote(italic(.(unique(df.i$nom_scien)))~.(years.)~"(N ="~.(nrow(df.i.narm))*")"))
print(barplot.i)
ggsave(paste0("Figs/Sc_nb_sp/", unique(na.omit(df.i$nom_scien)), "_", years.,"_barplot.png"), barplot.i, width = 5, height = 4)
}
}
size.sp.(df.fsh. = df.fsh.red, df. = df_sum, years. = "2020-2023")
## [1] "Coris julis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-10[ 5 0 0 0 0
## [10-12[ 0 11 0 0 0
## [12-15[ 0 0 21 0 0
## [15-18[ 0 0 0 23 0
## [18-22] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-10[ 0 0 0 0 0
## [10-12[ 0 0 0 0 0
## [12-15[ 0 0 0 0 0
## [15-18[ 0 0 0 0 0
## [18-22] 0 0 0 0 14
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Diplodus annularis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [5-8[ 1 0 0 0 0
## [8-12[ 0 21 0 0 0
## [12-15[ 0 0 0 0 0
## [15-17[ 0 0 0 0 0
## [17-20] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [5-8[ 0 0 0 0 0
## [8-12[ 0 0 0 0 0
## [12-15[ 0 0 17 0 0
## [15-17[ 0 0 0 5 0
## [17-20] 0 0 0 0 4
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Pagellus erythrinus"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [10-14[ 5 0 0 0 0
## [14-18[ 0 10 0 0 0
## [18-22[ 0 0 18 0 0
## [22-26[ 0 0 0 10 0
## [26-30] 0 0 0 0 7
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus cabrilla"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [4-8[ 2 0 0 0 0
## [8-12[ 0 16 0 0 0
## [12-15[ 0 0 16 0 0
## [15-19[ 0 0 0 35 0
## [19-23] 0 0 0 0 10
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus scriba"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [2-7[ 8 0 0 0 0
## [7-11[ 0 23 0 0 0
## [11-16[ 0 0 60 0 0
## [16-20[ 0 0 0 0 0
## [20-25] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [2-7[ 0 0 0 0 0
## [7-11[ 0 0 0 0 0
## [11-16[ 0 0 0 0 0
## [16-20[ 0 0 0 27 0
## [20-25] 0 0 0 0 18
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Spondyliosoma cantharus"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-13[ 12 0 0 0 0
## [13-19[ 0 13 0 0 0
## [19-24[ 0 0 0 0 0
## [24-29[ 0 0 0 0 0
## [29-34] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-13[ 0 0 0 0 0
## [13-19[ 0 0 0 0 0
## [19-24[ 0 0 7 0 0
## [24-29[ 0 0 0 4 0
## [29-34] 0 0 0 0 4
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
size.sp.(df.fsh. = df.fsh.red.1, df. = df_sum.1, years. = "2020-2022")
## [1] "Coris julis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 5
## [8-10[ 1 0 0 0
## [10-13[ 0 4 0 0
## [13-16[ 0 0 5 0
## [16-18[ 0 0 0 0
## [18-22] 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 5
## [8-10[ 0 0 0 0
## [10-13[ 0 0 0 0
## [13-16[ 0 0 0 0
## [16-18[ 0 0 0 0
## [18-22] 0 0 0 6
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Diplodus annularis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 3 4 5
## [5-8[ 1 0 0 0
## [8-12[ 0 0 0 0
## [12-15[ 0 0 0 0
## [15-17[ 0 0 0 0
## [17-20] 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 3 4 5
## [5-8[ 0 0 0 0
## [8-12[ 0 0 0 0
## [12-15[ 0 2 0 0
## [15-17[ 0 0 1 0
## [17-20] 0 0 0 2
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Loligo sp"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 2 4 5
## [16-19[ 0 0 0
## [19-22[ 1 0 0
## [22-24[ 0 0 0
## [24-27[ 0 2 0
## [27-30] 0 0 3
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Pagellus erythrinus"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [10-14[ 2 0 0 0 0
## [14-18[ 0 3 0 0 0
## [18-22[ 0 0 7 0 0
## [22-26[ 0 0 0 5 0
## [26-30] 0 0 0 0 1
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus cabrilla"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 2 3 4 5
## [4-7[ 0 0 0 0
## [7-10[ 2 0 0 0
## [10-14[ 0 4 0 0
## [14-17[ 0 0 14 0
## [17-20] 0 0 0 8
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus scriba"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [10-13[ 5 0 0 0 0
## [13-16[ 0 7 0 0 0
## [16-19[ 0 0 0 0 0
## [19-22[ 0 0 0 0 0
## [22-25] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [10-13[ 0 0 0 0 0
## [13-16[ 0 0 0 0 0
## [16-19[ 0 0 5 0 0
## [19-22[ 0 0 0 2 0
## [22-25] 0 0 0 0 1
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
size.sp.(df.fsh. = df.fsh.red.2, df. = df_sum.2, years. = "2023")
## [1] "Coris julis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-10[ 4 0 0 0 0
## [10-12[ 0 9 0 0 0
## [12-15[ 0 0 17 0 0
## [15-18[ 0 0 0 20 0
## [18-20] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-10[ 0 0 0 0 0
## [10-12[ 0 0 0 0 0
## [12-15[ 0 0 0 0 0
## [15-18[ 0 0 0 0 0
## [18-20] 0 0 0 0 8
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Diplodus annularis"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [8-10[ 9 0 0 0 0
## [10-12[ 0 12 0 0 0
## [12-14[ 0 0 0 0 0
## [14-16[ 0 0 0 0 0
## [16-18] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [8-10[ 0 0 0 0 0
## [10-12[ 0 0 0 0 0
## [12-14[ 0 0 11 0 0
## [14-16[ 0 0 0 6 0
## [16-18] 0 0 0 0 4
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Diplodus sargus"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [6-16[ 10 0 0 0 0
## [16-26[ 0 12 0 0 0
## [26-35[ 0 0 2 0 0
## [35-45[ 0 0 0 1 0
## [45-55] 0 0 0 0 1
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus cabrilla"
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [4-8[ 2 0 0 0 0
## [8-12[ 0 12 0 0 0
## [12-15[ 0 0 12 0 0
## [15-19[ 0 0 0 20 0
## [19-23] 0 0 0 0 5
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Serranus scriba"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [2-7[ 8 0 0 0 0
## [7-11[ 0 19 0 0 0
## [11-16[ 0 0 52 0 0
## [16-20[ 0 0 0 0 0
## [20-25] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [2-7[ 0 0 0 0 0
## [7-11[ 0 0 0 0 0
## [11-16[ 0 0 0 0 0
## [16-20[ 0 0 0 22 0
## [20-25] 0 0 0 0 15
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
## [1] "Spondyliosoma cantharus"
## , , mature = non
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-11[ 8 0 0 0 0
## [11-15[ 0 7 0 0 0
## [15-19[ 0 0 9 0 0
## [19-24[ 0 0 0 0 0
## [24-30] 0 0 0 0 0
##
## , , mature = oui
##
## tail_cm_classe.num
## tail_cm_classe 1 2 3 4 5
## [7-11[ 0 0 0 0 0
## [11-15[ 0 0 0 0 0
## [15-19[ 0 0 0 0 0
## [19-24[ 0 0 0 4 0
## [24-30] 0 0 0 0 3
## `summarise()` has grouped output by 'tail_cm_classe'. You can override using
## the `.groups` argument.
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red", "results_df", "results_df.1", "results_df.2")))
# plot CPUE ####
# Les captures par unités d’effort (CPUE) par techniques de pêches ont été exprimées en g.jour.pêcheur -1.
# Actually, CPUE in the db is calculated as poids_g/1.5/nb_pecheur ; so this is not the same unit actually ...?!
df. <- fishing[, c("a", "mod_peche", "nom_scien", "CPUE")]
unique(df.$a)
## [1] "2020" "2021" "2022" "2023" NA "2024"
table(df.$a)
##
## 2020 2021 2022 2023 2024
## 39 68 83 627 115
unique(df.$mod_peche)
## [1] "csm" "pe" "pdb" "po"
table(df.$mod_peche)
##
## csm pdb pe po
## 46 324 563 1
ggplot(filter(df., a %in% c("2020", "2021", "2022", "2023")), aes(x = mod_peche, y = CPUE, fill = mod_peche)) +
stat_boxplot(geom = "errorbar",
width = 0.25) +
geom_boxplot()
## Warning: Removed 579 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
## Warning: Removed 579 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
table(df.$mod_peche)
##
## csm pdb pe po
## 46 324 563 1
df.$mod_peche <- ifelse(df.$mod_peche == "csm", "chasse sous-marine", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pdb", "peche du bord", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "pe", "peche embarquée", df.$mod_peche)
df.$mod_peche <- ifelse(df.$mod_peche == "po", "peche à l'oursin", df.$mod_peche)
table(df.$mod_peche)
##
## chasse sous-marine peche à l'oursin peche du bord peche embarquée
## 46 1 324 563
df.$mod_peche <- as.factor(df.$mod_peche)
df.$mod_peche <- factor(df.$mod_peche, levels = c("chasse sous-marine", "peche du bord", "peche embarquée", "peche à l'oursin"))
table(df.$mod_peche)
##
## chasse sous-marine peche du bord peche embarquée peche à l'oursin
## 46 324 563 1
df. %>% filter(a %in% c("2020","2021","2022", "2023")) -> data.1
ggplot(filter(data.1, mod_peche != "peche à l'oursin"), aes(x=mod_peche, y=CPUE)) +
geom_boxplot() +
xlab("mode de peche") +
ylab("CPUE (poids (g) / 1.5 / nb pêcheurs)") +
ggtitle("2020-2023") +
ylim(0,max(data.1$CPUE, na.rm = T)*1.1) +
scale_x_discrete(drop=FALSE) +
scale_fill_manual(drop=FALSE) +
geom_point(data = filter(data.1, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = CPUE)) +
stat_summary(fun.y=mean, geom="point", shape=20, size=5, color="red", fill="red") +
geom_point(data = filter(data.1, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = mean(unclass((filter(data.1, mod_peche == "peche à l'oursin")["CPUE"]))$CPUE)), shape=20, size=5, color="red", fill="red") +
scale_y_cut(breaks = c(750), which=c(1), scales=c(0.5))
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
ggsave("Figs/CPUE/CPUE_2020-2023.png", width = 5, height = 4)
df. %>% filter(a %in% c("2020","2021","2022")) -> data.2
ggplot(filter(data.2, mod_peche != "peche à l'oursin"), aes(x=mod_peche, y=CPUE)) +
geom_boxplot() +
xlab("mode de peche") +
ylab("CPUE (poids (g) / 1.5 / nb pêcheurs)") +
ggtitle("2020-2022") +
ylim(0,max(data.2$CPUE, na.rm = T)*1.1) +
scale_x_discrete(drop=FALSE) +
scale_fill_manual(drop=FALSE) +
geom_point(data = filter(data.2, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = CPUE)) +
stat_summary(fun.y=mean, geom="point", shape=20, size=5, color="red", fill="red") +
geom_point(data = filter(data.2, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = mean(unclass((filter(data.2, mod_peche == "peche à l'oursin")["CPUE"]))$CPUE)), shape=20, size=5, color="red", fill="red") +
scale_y_cut(breaks = c(750), which=c(1), scales=c(0.5))
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
ggsave("Figs/CPUE/CPUE_2020-2022.png", width = 5, height = 4)
df. %>% filter(a %in% c("2023")) -> data.3
ggplot(filter(data.3, mod_peche != "peche à l'oursin"), aes(x=mod_peche, y=CPUE)) +
geom_boxplot() +
xlab("mode de peche") +
ylab("CPUE (poids (g) / 1.5 / nb pêcheurs)") +
ggtitle("2023") +
ylim(0,max(data.3$CPUE, na.rm = T)*1.1) +
scale_x_discrete(drop=FALSE) +
scale_fill_manual(drop=FALSE) +
geom_point(data = filter(data.3, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = CPUE)) +
stat_summary(fun.y=mean, geom="point", shape=20, size=5, color="red", fill="red") +
geom_point(data = filter(data.3, mod_peche == "peche à l'oursin"),
mapping = aes(x = mod_peche, y = mean(unclass((filter(data.3, mod_peche == "peche à l'oursin")["CPUE"]))$CPUE)), shape=20, size=5, color="red", fill="red") +
scale_y_cut(breaks = c(750), which=c(1), scales=c(0.5))
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
ggsave("Figs/CPUE/CPUE_2023.png", width = 5, height = 4)
rm(list=setdiff(ls(), c("fishing", "fishing.PNMCA", "fishing.Stareso", "Meta.survey", "survey", "%notin%", "df.msa", "df.mod", "df.mod.short", "multinom_model.short.red", "df.mod.large", "multinom_model.large.red", "results_df", "results_df.1", "results_df.2")))